TW200912002A - Predicting post-treatment survival in cancer patients with microrn - Google Patents

Abstract

This invention provides a method for predicting the post-treatment survival prospect of a cancer patient based on the expression level(s) of microRNAs hsa-miR137, hsa-miR372, hsa-miR182*, hsa-miR221, and hsa-let-7a in that cancer patient.

Description

200912002 IX. DESCRIPTION OF THE INVENTION: TECHNICAL FIELD OF THE INVENTION The present invention relates to a method for predicting survival prospects of cancer patients after treatment. [Prior Art] Lung cancer, especially non-small-cell lung cancer (NSCLC), is the most common cause of cancer death in the world, see Jemal et al., CA Cancer J_Clin. 56: 106-130 (2006). Early NSCLC patients have a recurrence rate of approximately 40% within 5 years of treatment; studies indicate that disease progression may be associated with clinical outcomes, see Miller, Am. J. Respir. Cell Mol_ Bi〇i. 33:216-223 (2005 ). However, this factor alone cannot predict clinical prognosis alone. Studies have shown that gene expression profiling, particularly microRNA (miRNA) profiling, can be used for cancer diagnosis and prognosis, see Endoh et al_, J. Clin Oncol 22: 811-819 (2004); Potti et al" Ν Engl. J. Med. 355: 570-580 (2006). For example, when deciding to determine a subpopulation of cancer, it has been found that certain microRNAs behave in a manner comparable to other encodeable proteins. The gene is more precise, see Calin et al., Nat. Rev. Cancer 6:857-866 (2006); and Volinia et al., Proc. Natl. Acad. Sci. USA 103:2257-2261 (2006). Ribonucleic acid is a small RNA that cannot encode proteins, but can regulate the expression of hundreds of genes after transcription by RNA interference. Thus, 200912002 can control a large number of biochemical reaction pathways, such as cell proliferation, differentiation and apoptosis. , see Calin et al., 2006. Studies indicate that certain microribonucleic acid signatures, ie one or more microRNAs that exhibit a specific pattern of expression in a population of patients, and chronic lymphocytic leukemia, lung adenocarcinoma For clinical prognosis of breast cancer and pancreatic cancer, see Calin et al., 2006. In view of this, it is urgent to identify new microribonucleic acid signatures in related fields because these microribonucleic acid signatures can be effectively used to predict various cancers. In particular, the clinical prognosis of NSCLC. SUMMARY OF THE INVENTION The present invention finds that certain microRNAs, such as hsa-miR137, hsa-miRNA372, hsa-miR182*, hsa-miR221, and hsa-let-7a, are expressed in a cancer Survival prospects for treatment after treatment. One aspect of the present invention provides a method for predicting survival after treatment in a cancer patient. The method is based on hsa-miR137, hsa-miR372, hsa-miR182*, hsa-miR221 or The amount of hsa-let_7a, which determines the normalized threshold cycle value (-dCt). If the hs-miR137, hsa-miR182* and hsa-miR372 have a -dCt value equal to or less than -8.22, -7.83&-11.25, respectively; 4Shsa When the -miR221&hsa-let-7ai-dCt values were equal to or greater than -0.57 and 2.21, respectively, it was determined that the patient's survival prospect after treatment was acceptable (a fair prospect). According to another aspect of the present invention, the survival prospect of a cancer patient can be predicted based on the amount of expression of four microribonucleic acids selected from the group consisting of hsa-miR137, hsa-miR372, hsa-miR182. *, 200912002 hsa-miR221 and hsa-let-7a. Specifically: 1. When investigating the performance of hsa-miR372, hsa-miR182*, hsa-miR221, and hsa-let-7a, the risk score is calculated as follows: (0.31 X hsa-miR372 Performance) + (0.28 x hsa-miRlS) * performance) + (-0.13xhsa-miR221 performance) + (-0.14 X performance amount of hsa-let-7a). A risk score equal to or less than -5.90 indicates that the patient's survival prospect after treatment is acceptable. 2. When investigating the performance of hsa-miR137, hsa-miR182*, hsa-miR221 and hsa-let-7a, the risk integral is calculated as follows: (0·15χ hsa-miR137 performance) + ( 0.28 x hsa -miRl82* performance) + ( -0.13 X hsa-miR221 performance) + (-0.14 x performance amount of hsa-let-7a). A risk score equal to or less than -3.71 indicates that the patient's survival prospect after treatment is acceptable. 3. When investigating the performance of hsa-miR137, hsa-miR372, hsa-miR221 and hsa-let-7a, the risk integral is calculated as follows: (0·15χ hsa-miR137 performance) + ( 0_31 x hsa- The amount of performance of miR3 72) + (the performance of -0·13 X hsa-miR221) + (-0.14 x performance amount 〇£118 &- to -73). A risk score equal to or less than -4.87 indicates that the patient's survival prospect after treatment is acceptable. 4. When investigating the performance of hsa-miR137, hsa-miR182*, hsa-miR372 and hsa-let-7a, the risk integral is calculated as follows: (0·15χ hsa-miR137 performance) + (0.28 X hsa -miR182* performance) + (0.31 X hsa-miR372 performance) + (-0·14χ performance of 1^3-^-73). A risk score equal to or less than -7.02 indicates that the patient is treated after the 200912002 live outlook is acceptable. 5. When investigating the performance of hsa-miR137, hsa-miR182*, hsa-miR221 and hsa-miR372, the risk integral is calculated as follows: \〇15 X hsa-miR137 performance) + ( 0.28 x hsa-miRl82* The amount of performance) + (the performance of -0_13 X hsa-miR221) + (the performance of 〇3lx hsa-miR372, the risk score is equal to or less than -6 86 indicates that the patient's survival prospect after treatment is acceptable. According to the present invention In one aspect, the survival prospects of cancer patients are predicted based on the performance of the above five microribonucleic acids. The risk scores are calculated as follows: (0_15xhsa-miR137 performance) + (〇31χ performance ofhsa-miR372) + ( 〇·28χ Performance + (-表现_13 x hsa-miR221 performance) + (-〇.l4x performance amount ofhSa-let-7a). If the cancer patient's risk score is equal to or greater than _7_b Survival prospects for cancer patients after treatment are still acceptable. According to yet another aspect of the present invention, the survival prospects of cancer patients are predicted based on the amount of hsa_miR221, hsa-miR372 and hsa-miRl37. The risk scores are calculated as follows: (〇15xhsa_miRi37 performance) + (0_31x table ofhsa_miR372) + (_〇13χ hsa-miR221 performance> If the cancer patient's risk score is equal to or less than -4.7, the cancer patient's survival prospect after treatment is acceptable. A cancer patient's survival prospect after treatment "Acceptable" means that the risk of death from treatment is reduced by at least 5% (eg, 1% or 150%) compared to the average risk of death in patients with the same type of cancer. 200912002 In the present invention, another type of (4) is used in the case of the use of the "fourth" sugar nucleic acid in the 'group'. In the embodiment, the above set includes a plurality of oligos (four), which can be used to detect hsa-miR22 and hsa_miR372 and its performance. In one embodiment, the kit comprises a plurality of oligonucleotides, which can be used to detect the expression of at least four microribonucleic acids selected from the group consisting of hSa-miR137, hsa_miR372, and hSa-let-7a. The oligonucleotides contained in the kit are immobilized on a support member (eg, a polymeric substrate) to form a nucleic acid wafer. Experienced (eg, surgical treatment, chemotherapy, or radiation) Treatment) of cancer Originally of lung cancer (e.g., each of the non-small cell lung cancer), leukemia, breast, pancreas, adenocarcinoma or squamous cell carcinoma, colon cancer, or hepatocellular carcinoma. One or more specific embodiments of the invention are set forth below. Other features, objects, and advantages of the invention will be apparent from the embodiments and appended claims. D [Embodiment] The present invention provides a method for predicting a clinical prognosis (e.g., post-treatment survival prospect) of a cancer patient, the method being based on a performance pattern of one or more microribonucleic acids associated with the clinical prognosis. The following method can be used to identify one or more microRNAs associated with clinical desire. Raise a group of treated cancer patients. Patients with the same type of cancer were randomly assigned to the training group and the test group. Using the known method of the 200912002 method, the cancer tissues/cells (for example, living tissue, specimen, nail-fixed tissue, or cold; bundles) are included in the two groups. The amount of microRNA expression. The above known methods are, for example, or microarray analysis. Therefore, the amount of expression per ribonucleotide in the same patient can be standardized by internal control such as the amount of expression of n Go UO to obtain a standardized expression amount. Statistical methods such as Cox regression analysis are used to analyze the amount of standardized microRNAs obtained from the training group to determine which microRNAs are associated with the clinical outcome of the cancer patient (eg, post-treatment survival status). In one embodiment, the hazard ratios obtained by univariate cox regression analysis are used to identify the microRNAs associated with death. [The above deaths may be due to cancer recurrence or any other original

Because 'see Cox, J. Royal Statistical Society Series B 34: 187-220 (1972). If the risk ratio of the microribonucleic acid is less than 丨, the microribonucleic acid is classified as a protective microribonucleic acid, and if the dangerous ratio of the micronucleic acid nucleic acid is greater than 1, the microRNA is classified as a risk micro Ribonucleic acid. Once micronuclei nucleic acids (eg, protective and risk microRNAs) associated with clinical prognosis are identified, statistical analysis methods known in the relevant art can be used to determine the relationship between the performance pattern and clinical outcome of the microribonucleic acid. Correlation. In one embodiment, the risk score for each patient is calculated based on the amount of performance of one or more protective and/or risk-type microribonucleic acids, and thereafter the risk integral value and a patient's treatment are determined Relationship during survival. Verifying the phase determined by the above method in the test population to confirm that the microRNA expression pattern is indeed related to the clinical prognosis in the study. In a preferred case, the above correlation can be further verified in an independent cohort, which includes a group of patients whose cancer type is the same as that of the training group and the test group. . After verification, and in the preferred case, after confirmation, the identified microRNAs can be used to predict the clinical prognosis of patients with the same cancer type based on their performance patterns. For example, a mathematical formula can be constructed to take into account both the performance of these microRNAs and their significance in statistical analysis. Using the above mathematical formula, the risk score of the patient can be calculated. The risk score value can indicate the clinical prognosis of the patient. MicroRNAs associated with the clinical prognosis of cancer patients can also be used to identify possible targets for cancer treatment, see Czech, N. Engl. J. Med. 354: 1194-1195 (2006). Target genes for these miniribonucleic acids can be identified using a prediction algorithm using miniRNA symbols, such as PicTar, see Krek et al., Nat. Genet. 37:495-500 (2005); TargetScan, see Lewis et al., Cell 115: 787-798 (2003); miRNAMap, see Hsu et al., Nucleic Acids Res. 34: D135-139 (2006); miRBase, see Griffiths-Jones et al., Nucleic Acids Res. 34: D140-144 (2006); GenMAPP, see https://www.genmapp.org; and Reactome, see https://www_reactome.org. These genes and their products are possible targets or drugs for cancer treatment. Embodiments of the present invention can be easily understood from the above description. The following examples illustrate the microRNA signatures that can be used to predict survival prospects for nsclc patients after treatment. This embodiment is for illustrative purposes only and is not intended to limit any other part of the specification. All publications mentioned in the specification are incorporated as a reference for the present invention. Materials and Methods (a) Patient and Tissue Samples 112 all NSCLC patients who had undergone surgical resection were recruited from Taichung Veterans General Hospital. These patients were randomly assigned to the training group data set («=5〇 and test group data sets. In addition, 62 NSCLC patients who also undergo surgical resection were recruited by the Taiwan University Medical College, using these 62 patients as independent Peer group. Frozen lung cancer tissue samples were obtained from all recruited patients. All patients were Han Chinese. (b) MicroRNA mapping analysis using ABI PRISM 7900 real-time PCR system and TaqMan MicroRNA Assays Human Panel- Early Access Kit The group (hereafter referred to as the TaqMan kit) performs microRNA expression mapping. The TaqMan kit contains primers that can be used to determine 157 adult microRNAs (Applied Biosystems). Use TaqMan microRNA RT reagents and specialize for a microRNA. The primer is used to amplify the cDNA of each microribonucleic acid and further amplified by TaqMan 2x Universal PCR Master mix. During the amplification process, the fluorescent dye is added to the cDNA product. The amount of each microribonucleic acid is Expressed by a threshold cycle (Ct) value based on the fluorescent dye added to the cDNA product 13 200912002 Determined by the amount of fluorescence. ct is the fraction of the amount of fluorescence exceeding a fixed threshold. The Ct value of each microribonucleic acid is then normalized by the Ct value of U6. U6 is a quantitative analysis of microribonucleic acid. A commonly used internal control, see Jiang et al., Nucleic Acids Res. 33:5394-5403 (2005); and Yanaihara et al., Cancer Cell 9:189-198 (2006). Specifically, normalized Ct values (- dCt) is calculated as follows: -dCt = (Ct microribonucleic acid-Ctu6) (c) Statistical analysis uses the hazard ratio obtained by univariate Cox regression analysis to identify the amount of performance and the patient's post-treatment death/survival status Related microRNAs (in order to reduce false positive results 'using a permutation test to evaluate the P value of a univariate Cox regression value for each microribonucleic acid, with the survival of the patient, together with the limits State, randomly arranged for a total of 10,000 iterations. Construct a mathematical formula to calculate the risk score for each patient. The above formula needs to consider one or more micro-identifications identified after death/survival status after treatment. The amount of expression of ribonucleic acid and the regression coefficients obtained by the above univariate Cox regression analysis are described in Lossos et al., N. Engl. J. Med. 350:1828-1837; and Cox, 1972. The patient's risk score is related to the patient's post-treatment survival period: for patients with higher risk scores, the expected post-treatment survival period is shorter; and for patients with lower risk scores, the expected post-treatment survival period is higher. long. All participating patients were classified as high risk groups and low risk based on the patient's risk score. In the analysis of 14 200912002 differences in patient characteristics between high-risk groups and low-risk groups, the continuous variables were analyzed using the Student's ί test, and the Fisher's exact test was used for the category variables (Fisher's exact test). ) for analysis. The Kaplan-Meier method was used to estimate the overall survival status of the patients in the above two groups and the status of non-recurring survival. Log-rank tests were used to analyze differences in overall survival and non-recurring survival between patients in the two cohorts. All data obtained from the training data set using the above method can be verified and confirmed in the test data set and the patients of the independent peer group. Multivariate Cox proportional hazard regression analysis and stepwise variable selection were performed to assess the extent of individual outcome factors associated with individual patient survival status. Micronucleic acid signature risk scores, age, gender, number of cancer stages, and histological analysis were used as covariates. All of the above analyses were performed using SAS software (version 9.1, issued by SAS Institute Inc.). A two-tailed assay was performed and P < 0.05 indicates that the test results were statistically significant. Results (a) Identification and confirmation of a microribonucleic acid signature to predict overall survival and non-recurrent survival status of NSCLC patients Table 1 illustrates the clinical characteristics of 56 NSCLC patients in the training data set and 56 NSCLC patients in the test data set. In terms of clinical features, there was no significant difference between the two groups of data sets. Table 1: Clinical pathological features of 112 NSCLC patients. Training data set Number of patients (%) Number of patients (%) 15 200912002 n=56 η=56 Age* 66.5 ±10·0 65.3 Soil 14.1 0.606 f Gender male 45 (80) 43 (77) 0.818ί Female 11 (20) 13 (23) Cancer number first collapse 21 (38) 26 (46) 0.5491 Second issue 14 (25) 14 (25) Third 21 (37) 16 (29) Cell type adenocarcinoma 25 (45) 30 (53) 0.1501 Squamous cell carcinoma 25 (45) 25 (45) Other 6 (10) 1 (2) * by mean ± standard The deviation (SD) indicates that t is performed on the Shi's test. F is performed on the Fischer's exact test using the method described above to determine the amount of microribonucleic acid expression in all patients. Data from the training data set were subjected to univariate Cox regression analysis to identify microRNAs with expression levels associated with post-treatment death/survival status. The trial found that there are five microRNAs associated with the overall survival status of the patients in the training data set. The five microRNAs are hsa-miR137, hsa-miR372, hsa-miR182*, hsa-miR221 and hsa-let-7a. . Among them, the first three are high-risk microRNAs, and the latter two are protective microribonucleic acids. Based on the performance of these five microRNAs, the risk score for the patient can be calculated using the following formula: (0.15 X hsa-miR-137 performance) + (0.31xhsa-miR-372 performance) + (0.28xhsa -miR-182* 16 200912002 performance) + (-〇.13xhsa-miR-221 performance) + (-0.14 X hsa-let-7a performance). Patients with a risk score greater than 7.1 were classified as high-risk groups, and patients with a risk score less than 7.1 were classified as low-risk groups. Table 2 illustrates the clinical characteristics of patients in high-risk and low-risk groups. Table 2: Clinical features of NSCLC patients with high-risk and low-risk data

Characteristic high risk group low risk group P value training data set (/*=56) n=28 n=28 age* 65.7 ±10.3 67.3±9.7 0.549卞 to male 21 (75) 24 (86) 0.503ί Female 7 ( 25) 4 (14) First stage of cancer 5 (18) 16 (57) 0.0081 Second stage 8 (28) 6 (22) Third stage 15 (54) 6 (21) Cell type adenocarcinoma 15 (54 10 (36) 0.3531 Squamous cell carcinoma 10 (36) 15 (54) Other 3 (10) 3 (10) Test data set 0=56) n=26 n=30 Age* 66.5±13.6 64.3±14.7 0.57 f Gender male 22 (85) 21 (70) 0.2241 Female 4 (15) 9 (30) Number of cancer stages 1 (42) 15 (50) 0.3401 17 200912002

Phase 2 5 (19) 9 (30) Phase 3 10 (39) 6 (20) Cell Type Adenocarcinoma 17 (65) 13 (43) 0.1791 Squamous Cell Carcinoma 9 (35) 16 (53) Other 〇 (〇) 1 (4) Independent peer group (/1=62) η=40 η=22 Age* 62_9±10_3 64_1土9.1 0_634卞 Gender male 32 (80) 10 (45) 0.010? Female 8 (20) 12 (55) The first phase of cancer 15 (37) 13 (59) 0.1521 Second phase 6 (15) 4 (18) Phase III 19 (48) 5 (23) Cell type adenocarcinoma 21 (52) 9 ( 41) 0.5631 squamous cell carcinoma 13 (33) 8 (36) Others 6 (15) 5 (23) * Expressed by mean ± standard deviation (SD) t for the Shi's test 1 for Fisher's exact test 1A Figures to Figure 1C illustrate the risk scores, survival status, and microRNA performance analysis profiles for NSCLC patients in the training and test data sets, respectively. Among the patients with high-risk scores, the three high-risk microribonucleotides showed higher performance and the two protective microRNAs had lower performance. Conversely, in patients with low-risk scores, the performance of the three high-risk microRNAs was low, and both protective microRNAs 18 200912002 had higher performance. In the training data, the high suture group and the low-test phase were compared, and the former had a shorter survival period after surgery. Referring to Figure 2A, the median overall survival of patients with high-risk groups was approximately 2G months, while the median overall survival of the low-risk group was greater than % m without recurrence. The number of patients in the high-risk group was about 10 months, while those in the low-risk group were more than 45 months (see Figure 2A). _ 闽; the above results are not obvious, using the aforementioned five micro-ribonucleic acid expression patterns (ie, micro-ribonucleic acid characteristics), patients can be classified into high-risk or low-risk groups, and such micro-ribonucleic acid characteristics and cancer patients The survival period after treatment is related. Wangmen verified the micronucleic acid characteristics and survival of the above-mentioned micrographs. The data of the Tianjibeiji collection was similar to that of the training data, and it also showed that the low-risk group survived after treatment: patients (see the figure). In the high-risk group disease, the median overall survival was about 25 months, and the median was about 14 months. In the low-slaughter, the median survival and the median survival of the patients were more than 5G months and 4G months, respectively. All of the above results are statistically significant.

The above 24C〇X regression analysis showed that among the factors listed in Table 3, only the above-mentioned microribonucleic acid characteristic fish N in C patients had an overall survival state c hazard ratio [TM]=10·31'ρ=0 002 ) related. Table 3: NSCLC Cox regression* analysis of multivariate variability and survival status of patients with microRNAs 200912002 Variable hazard ratio 95% CI 整体 overall survival status training data set 0=56) MicroRNA performance characteristics 10.31 2.33-45.56 0.002 Test data set ("=56) microribonucleic acid performance characteristics 3.65 1.29-10.37 0.015 cancer stage 8.12 2.83 -23.25 <0.001 age 1.08 1.03-1.14 0.002 independent cohort ("=62" microRNA performance characteristics 2.81 1.13- 7.01 0.026 Cancer stage 2.35 1.13-4.89 0.022 Non-recurrent survival status training data set MicroRNA performance characteristics 3.29 1.24-8.71 0.016 Cancer stage 2.63 1.10-6.25 0.029 Test data set ("=56" MicroRNA performance characteristics 2.86 1.20 -6.82 0.018 Number of cancer stages 2.97 1.32-6.69 0.009 Characteristics of microribonucleic acid expression in independent age group 2.39 1.12-5.10 0.024 Number of cancer stages 2.76 1.43-5.34 0.003 Age 0.93 0.90 - 0.97 <0.001 *Selective change using stepwise variable selection method item

(b) Verification of microribonucleic acid signatures that can be used to predict survival in independent cohorts Verify whether the above microRNA signature can be used to predict post-treatment survival status in independent cohorts, including 62 NSCLC patients. The clinical characteristics of these 62 patients are listed in Table 2 above. Using the method described above, the risk score for each patient was calculated based on the patient's five microRNA performance patterns. Patients with a risk score greater than 7.1 were classified as 20 200912002 high-risk groups, and patients with a risk score less than 7.1 were classified as low-risk groups. As shown in Figure 2C, the high-risk group compared with the low-risk group patients, the former had a shorter survival after treatment, and the median survival of the two groups was about 40 months and more than 120 months, respectively. The median number of unrecurring survival in the two groups was 20 months and 48 months, respectively. Multivariate Cox regression analysis showed that microRNA characteristics and number of cancer stages were associated with overall survival and non-recurring survival status (see Table 3 above). These results confirm that the microRNA signature described above can be used to predict post-treatment survival prospects for cancer patients. (c) Correlation between microRNA characteristics and post-treatment survival prospects for NSCLC patients with different cancer stages and histological subgroups. Using the methods described above, different cancers will be based on the patient's microribonucleic acid characteristics. The number of patients and the NSCLC patients with histological subgroups were classified as high-risk and low-risk groups. As shown in Figures 3A through 3E, patients with low-risk groups survived longer after treatment than patients at high-risk groups. These results show that microRNA characteristics can also be used to predict the number of different cancer phases, namely, Phase I, Phase II, and Phase III; and different histological subpopulations, NSCLC of adenocarcinoma or squamous cell carcinoma subpopulations. Prospects for survival after treatment of patients. (d) Univariate Cox regression analysis using microRNA signature as a predictor of survival prospects for NSCLC patients revealed that the above five microRNAs, hsa-miR137, hsa-miR372, hsa-miR182*, hsa-miR221 or hsa The amount of performance of each of -let-7a is related to the survival state of NSCLC (see Table 4). Log-rank analysis shows that the mini-ribonucleic acid signature consisting of the above five 21 200912002 miniribonucleic acids is most suitable for predicting disease survival (see also Table 4). In addition, 'univariate Cox regression analysis showed that the microRNA characteristics consisting of any four of the above five microribonucleic acids were also associated with patient survival after treatment (see Table 5) » Table 4: Five of the NSCLC patients MicroRNA characteristics relative to individual microribonucleic acid expression Kaplan-Meier survival prospect analysis logarithmic rank-checked eigenvalue ribonucleic acid* training data set 丨 test data set independent peer group-:~:---- Overall survival state of five microRNAs 0.001 0.008 0.007 hsa-miR-221 0.021 0.264 0.955 hsa-let-7a 0.906 0.292 0.356 hsa-miR-137 0.026 0.347 0.005 hsa-miR-372 0.358 0.011 <0.001 bsa-miR -182* 0.126 0.005 0.904 —---....... no 4 recurrence survival state stomach five micro-nucleic acid 0.002 0.003 0.037 hsa-miR-221 0.008 0.680 〇 751 hsa-let-7a 0.258 0.225 υ. 461 hsa-miR-137 0.086 0.619 0.007 nsA-miK"^ /z hsa-miR-182* 0.615 0.005 Λ AAC 0.003 *: with a median ij divided into two groups U.UUD _ . . __〇^61 5: Five microRNA features in NSCLC patients Kaplan-Meier survival prospect analysis of the log-ranked cadaveric training data set test data set relative to the four micro-ribonucleic acid characteristics __ independent peer group whole survival state five micro-ribonucleic acid<0.001 0.008 0.007 --- - any of the five microRNAs "―'-___ ---~- 22 200912002 hsa-miR137, hsa-miR372, hsa-miR182* and hsa-let-7a <0.001 0.007 0.022 hsa- miR137 ' hsa-miR372 ^ hsa-miR182* and hsa-miR221 0.001 0.006 0.057 hsa-miR372, hsa-miR182*, hsa-miR221 and hsa-let-7a 0.020 0.038 0.058 hsa-miR137, hsa-miR182*, hsa-miR221 And hsa-let-7a 0.022 0.141 0.100 hsa-miR137, hsa-miR372, hsa-miR221 or hsa-let-7a <0.001 0.204 0.003 no recurrence of viable state five microRNAs 0.002 0.003 0.037 five microRNAs four of them lisa-miR137, hsa, miR372, hsa-miR182* and hsa-let-7a 0.012 0.013 0.078 hsa-miR137, hsa-miR372, hsa-tniR182* and hsa-miR221 0.033 0.008 0.154 hsa-miR372, hsa-miR182*, hsa-miR221 and hsa-let-7a 0.139 0.006 0.189 hsa-miR137 ' hsa-miR182* ' hsa-miR221 and hsa-let-7a 0.037 0.441 0.116 hsa-miR137, hsa_miR372, hsa-miR221 or hsa-let-7a <0.001 0.048 0.015 (e) Microribonucleic acid The putative gene targets were predicted using the GeneSpring pathway annotation software (issued by Silicon Genetics) to predict the putative pathways that may be involved in the above five microRNAs, and the results obtained using this software are summarized in Tables 6 and 7 below. Table 6: Target Genes for Predicted MicroRNAs 23 200912002

Miniature ribonucleic acid gene symbol unique gene database encoding algorithm ^ Path t GO** Biochemical reaction GO Molecular function GO cell composition let-7a ABCB9 Hs.511951 4 ABC transport protein - general type 02010 GO: 6857 GO: 15031 GO: 7283 GO:5524 GO:16887 GO:42626 GO: 166 GO:15198 GO:5215 GO:43190 GO:5783 GO:16021 GO:5764 let-7a ABCC10 Hs.55879 4 ABC Transport Protein - General 02010 GO:6810 GO: 5524 GO:16887 GO:42626 00:166 GO:16021 let-7a ABCC5 Hs.368563 4 ABC transport protein - general type 02010 GO:6810 00:5524 GO:16887 GO:42626 GO: 15239 GO: 166 GO:8514 GO : 16021 GO:5887 GO:5624 let-7a ATP2A2 Hs.506759 4 Calcium ion signal transmission path 04020 GO:6816 GO:6812 GO:7155 GO:8544 GO:8152 GO: 15992 GO:5524 GO:48155 GO:5509 GO :5388 GO:16787 GO:16820 G0.287 GO: 166 GO:5887 G0:16020 GO:5624 GO:5792 GO:16529 let-7a BZW1 Hs.355983 4 GO:6446 GO:3743 let-7a CDC25A Hs.1634 4 cell cycle 04110; cell cycle 69278; cell cycle checkpoint 69620 GO: 51301 GO:8283 GO:7067 GO:6470 GO:79 GO:16787 GO:4725 GO:8372 GO:5622 let-7a CHD4 Hs.162233 4 GO: 6333 GO: 16568 G0: 7001) GO: 6357 GO: 6350 GO: 5524 G0: 4003 GO: 3677 GO: 3682 GO: 16787 GO: 46872 GO: 785 GO: 5634 24 200912002

GO: 166 GO:5515 GO:8270 let-7a CHD9 Hs.59159 4 GO:6333 GO:5524 GO:3677 00:3682 GO:4386 GO:785 GO: 16021 GO:5634 let-7a CHRD Hs.166186 4 TGF -beta message path 04350 GO:7275 GO:1501 00:5554 GO:8372 let-7 a DHX57 Hs.468226 4 let-7 a DTX2 Hs.187058 4 Notch message path 04330 GO:7219 GO:16567 GO:46872 GO:4842 GO:8270 GO:5634 GO:151 let-7a E2F5 Hs.445758 4 Cell cycle 04110; TGF-beta message path 04350; cell cycle 69278 GO:74 GO:6355 GO:6350 GO:5515 G0:3700 GO:5634 GO:5667 let-7 a EZH2 Hs.444082 4 GO:6325 GO:6355 GO.6350 GO:3677 GO:5634 let-7a FASLG Hs.2007 4 Apoptosis 04210; Cytokine-cytokine receptor Interaction 04060; MAPK signal transduction path 04010; natural killer cell vector cytotoxicity 04650; type 1 diabetes 04940; apoptosis 109581 GO: 6915 GO: 7267 GO: 6955 GO: 6917 GO: 43123 GO: 7165 GO.-5164 GO:5615 GO:5887 G0:16020 let-7 a GALE Hs.557524 4 Galactose metabolism 00052; nucleotide sugar metabolism 00520; saccharide metabolism 71387 GO:5975 GO:6012 GO:9225 GO:51287 GO:39 78 GO;3824 GO:16853 let-7a GIPC1 Hs.6454 4 mRNA synthesis regulation GO:7186 GO:5515 GO:5102 GO:5829 GO: 16020 GO:5624 GO:5625 let-7a GOLT1B Hs'62275 4 GO:43123 GO: 16192 GO: 4871 GO: 16021 25 200912002

Let-7a HOXC11 Hs. 127562 4 GO:7275 GO:7492 GO:6355 GO:3702 G0:3700 GO:5634 let-7a IDH2 Hs.513141 4 Krebs TCA cycle; citric acid cycle; glutamine-based sulfur metabolism; Fixed cycle let-7a JMJD1A Hs.531819 4 let-7a LOC1515 79 Hs.529231 4 let-7a LRIG3 Ks.253736 4 let-7a MAP4K3 Hs.468239 4 MAPK message path 04010 GO:7254 GO:6468 GO:7243 GO :6950 GO:5524 GO:166 GO:4674 GO:5Q83 GO: 16740 let-7a MESDC1 Hs.513071 4 let_7a MLL5 Hs.567540 4 GO:6355 GO:5515 GO:8270 let-7a NDST2 Hs.225129 4 Chondroitin / Heparin sulfate biosynthesis 05532 GO: 8146 GO: 16740 GO: 5795 GO: 16021 let-7a NID2 Hs.369840 4 GO: 7155 GO: 7160 GO: 5509 GO: 5518 GO: 5604 GO: 16020 let-7a PBX3 Hs.428027 4 GO:7387 GO:9790 G0:30902 GO:7388 GO:6355 GO:45898 GO:5515 G0:3700 GO:5634 let-7a RANBP2 Hs.199561 4 GO:46907 GO:6457 00:6606 GO: 8536 GO: 5488 GO: 16853 GO: 46872 GO: 3755 GO: 8270 GO: 5643 GO: 5634 let-7a RFXDC1 Hs.352276 4 GO: 6355 GO: 6388 GO: 6350 GO: 3677 GO: 213 GO: 214 26 200912002

Let-7 a SEMA4C Hs.516220 4 Axon guidance 04360 GO:30154 GO:4872 GO: 16021 GO:7399 GO: 16020 let-7a SLC20A1 Hs. 187946 4 let-7a SLC35D2 Hs.494556 4 GO:4 GO: 5338 GO:8372 let-7a SOCS1 Hs.50640 4 Insulin message path GO:7259 GO:5159 QO:5131 04910 ; Jak-STAT message GO:7242 GO:19901 Conduction path 04630; second GO:46426 GO:4860 Diabetes 04930 GO: 1558 GO: 6512 let_7a STXBP5 Hs.93534 4 let-7a TMEM2 Hs.494146 4 GO: l602l let-7a TRAPPC1 Hs.24379 4 let-7a TSCOT Hs.512668 4 let-7a TUSC2 Hs.517981 4 let -7a UHRF2 Hs.493401 4 let-7a USP21 Hs.8015 4 GO:6512 GO:4197 GO:8372 GO:6511 GO:8233 GO:5515 GO:4221 let-7a USP32 Hs. 132868 4 GO:6512 GO:5509 GO:6511 GO:4197 GO:4221 let-7a ACTA1 Hs.1288 3 Smooth hunger contraction; striated muscles GO:7517 GO:43531 GO:5884 Shrink G0:30240 GO:5524 GO:5856 GO:3774 GO: 1725 GO: 17022 GO: 5865 GO: 166 GO: 5515 00:5200 let-7a AC VR1B Ks.438918 3 Adhesive bonding 04520; Cell GO: 6468 GO: 5524 GO: 5887 Hormone-cytokine receptor mutual GO: 7178 GO: 287 GO: 16020 Moving 04060; MAPK Message GO: 30145 Conduction path 04010; GO: 166 TGF-beta message path GO: 4674 04350 00:4872 GO: 16740 27 200912002

GO:5024 let-7a AD AMI 5 Hs.312098 3 GO:7155 GO:7160 GO:6508 GO:17124 GO:46872 GO:4222 GO:5515 GO:8270 GO: 16021 let-7a ADRB2 Hs.2551 3 Calcium Message Transduction Path 04020; Neuroactive Ligand-Receptor Interaction 04080 GO: 7186 GO: 7188 GO: 187 GO: 7190 GO: 8333 GO: 7243 GO: 6898 GO: 7171) GO: 4941 GO: 5515 GO: 4872 GO : 1584 GO: 5768 GO: 5887 GO: 5764 GO: 5886 let-7a ANKFY1 Hs.513875 3 GO: 6897 GO: 46872 GO: 5515 GO.8270 GO: 10008 GO: 16020 let-7a ANKRD4 3 Hs.13308 3 let -7a AP1S1 Hs.489365 3 GO:6886 GO:6898 GO:5515 GO:8565 GO:30121 GO:5795 GO:5802 GO:59〇5 let-7a APBB3 Hs.529449 3 GO:5515 GO:5737 let-7a ARHGAP 20 Hs.6136 3 let-7a ARL5 Hs.470233 3 GO:6886 GO:7264 GO:5525 GO:166 let-7 a ARMC8 Hs.266826 3 let-7a ATXN1 Hs.434961 3 GO:3723 GO:5737 GO :5634 let-7a B3GNT6 Hs.8526 3 Blood type glycolipid biosynthesis-new lactose series 00602; keratan sulfate biosynthesis 00533 GO:30311 GO:8532 GO:l6757 00:5795 GO:30173 GO:16021 let-7a BCL2L1 Hs.516966 3 amyotrophic atherosclerosis 05030; fine Apoptosis GO: 6916 GO: 8637 GO: 42802 GO: 16021 GO: 16020 28 200912002

04210, Jsk-STAT message path 04630; neurodegenerative disease 01510; apoptosis 109581 GO:8634 GO:42981 GO:5741 GO:5739 let-7a BNC2 Hs.435309 3 GO:6355 GO:6350 GO:46872 GO :3676 GO:8270 GO:5634 let-7a BRD3 Hs.522472 3 GO:4 GO:5554 GO:5634 let-7a BTBD3 Hs.244590 3 GO:5515 let-7a BTG2 Hs.519162 3 GG:6281 GO:8285 GO:6355 GO:6350 G0:3700 let-7a BZW2 Hs.487635 3 let-7a Clorf22 Hs.523811 3 Amino sugar metabolism 00530; glycosaminoglycan degradation 0051; nucleotide sugar metabolism 00520 GO:5975 GO:6487 GO :6508 GO:5509 GO:16798 GO:4571 GO:8233 GO:5783 G0.16020 let-7a CALU Hs.7753 3 GO:4 GO:5509 GO:5794 GO:5783 Iet-7a CAP1 Hs.370581 3 GO: 7190 GO:7163 GO:7165 GO:3779 GO: 16020 let-7a CASKIN1 Hs.530863 3 GO:7165 GO:5515 GO:5737 let-7a CDC34 Hs.514997 3 Ubiquitin media proteolytic let-7a CDYL Hs.269092 3 GO:6333 GO:8152 GO:7283 GO:3824 GO:3682 GO:8233 GO:785 00:5634 let-7a COIL Hs.532795 3 GO:5634 let-7a COL15A1 Hs.409034 3 GO: 1525 GO:7155 GO:30154 GO:6817 GO:55 15 GO:5198 GO:5582 GO:5737 GO:5578) let-7a COL1A1 Hs. 172928 3 Cell Signaling 01430; ECM-Receptor Interaction 04512; GO:8544 GO:6817 GO:5201 G0.8147 GO:5581 GO :5584 29 200912002

Focus attachment 04510; hemostasis 109582 GO:7605 GO:1501 GO:5737 let-7a COL1A2 Hs.489142 3 Cellular communication 01430; ECM-receptor interaction 04512; Focus attachment 04510; Hemostasis 109582 GO:4GO:6817 GO.-7605 00:1501 GO:7169 GO:5201 GO:8147 GO:5581 GO:5584 GO:5737 let-7a COL24A1 Hs.47312 3 let-7a COL3A1 Ks.443625 3 Inflammatory response path let-7a COL4A1 Hs. 17441 3 GO: 6817 GO:5201 GO:5581 00:5587 GO:5737 let-7a COL4A2 Hs.508716 3 let-7a COL4A5 Hs.369089 3 let-7a CPA4 Hs.93764 3 GO:16573 GO:6508 GO:4182 GO:4180 GO :46872 GO:8237 GO: 8270 GO:8372 Iet-7a CPD Hs.446079 3 GG:650S GO:4182 GO:4187 GO:4180 GO:46872 GO: 8472 GO:8237 GO:8270 GO:16021 GO:5624 let_7a CPEB2 Hs.374216 3 let-7a CPEB3 Hs.131683 3 GO:3676 GO:166 let-7a CPEB4 Hs. 127126 3 let-7a CPM Hs.434948 3 let-7a CPSF4 Hs.489287 3 mRNA synthesis regulation GO:6397 GO :3723 GO:46872 GO:8270 GO:5634 let-7a CTNS Hs. 187667 3 GO:15811 GO:6520 GO.6810 GO:15184 GO:I602I GO:5765 30 200912002

Let-7a CYP46A1 Hs.25121 3 GO:6707 GO:6118 GO:6629 GO:7399 GO: 8202 G0:20037 GO:5506 GO:46872 GO:8395 GO:5783 GO:16021 GO:5792 let-7a DDEF1 Hs. 106015 3 GO:43087 GO:5096 GO:46872 GO:5515 GO:8270 GO: 16020 let-7a DDX19 Hs.221761 3 let-7a DIMT1L Hs.533222 3 let-7a DLC1 Hs.134296 3 GO:7010 G0:30308 GO:30155 GO:7165 GO:5100 GO:5515 GO:5737 GO:5576 let_7a DMD Hs.495912 3 Striated muscle contraction GO:4 GO:7016 GO:6936 GO:7517 GO:3779 GO:5509 GO:5554 00:5515 G0:5200 GO:8307 GO:5198 GO:8270 GO:8372 GO:5856 GO:16010 let-7a DMP1 Hs. 128556 3 GO:7155 GO:30198 GO: 1503 GO:5509 GO:5178 GO:5578) let- 7a DMTF1 Hs.558441 3 let-7a DOT1L Hs.465554 3 Amino acid degradation 00310 GO:16568 GO: 18024 GO:S\6S GO:16740 GO:5634 let-7a DPF2 Hs. 13495 3 GO:6915 GO:8624 GO: 6355 GO: 6350 GO: 46872 GO: 3676 GO: 5515 GO: 8270 GO: 5634 Iet-7a DPP3 Hs.502914 3 GO: 6508 GO: 4177 GO: 17039 GO: 46872 GO: 5737 31 200912002

GO:8237 GO:8270 let-7a DST Hs.485616 3 G0:30036 GO:7155 G0:7050 GO:7010 GO:7229 GO:45lQ4 GO:3779 GO:51015 GO:5509 GO:5178 GO:8022 GO:5515 00:5200 00:5604 GO:5737 GO:16023 GO:5856 GO:5615 G0:30056 GO:5911 let-7a DUSP1 Hs. 171695 3 Ion ion message conduction path; type 1 diabetes; calcium ion signal path le1> 7a DUSP16 Hs.536535 3 MAPK message path 04010 GO: 45204 GO: 45209 G0.188 GO: 6470 GO: 17017 GO: 16787 G0.5737 GO: 5634 let-7a DUSP9 Hs. 144879 3 MAPK message path 04010 GO: 7254 GO: 188 00:6470 GO:17017 G0.16787 G〇:5737 GO:5634 let-7a DYRK1A Hs.368240 3 Degradation of benzoate by coenzyme (CoA) 00632; metabolism of inositol 00562; Nicotinic acid and nicotine guanamine metabolism 00760; phospholipid 醯 inositol signaling system 04070 GO: 7399 GO: 18108 G 〇: 5524 GO: 4715 GO: 166 GO: 4674 GO: 16740 GO: 5634 let-7a EGR3 Hs .534313 3 GO:7623 GO.-7517 GO:6355 GO:6350 GO:46872 G0;3700 GO:8270 GO:5634 let-7a EIF2C1 Hs.22867 3 GO:6412 GO:6446 GO:5515 GO:3743 GO: 5850 let-7a EIF2C3 Hs.56776 1 3 GO:6412 GO:3743 let-7a EIF2C4 Hs.471492 3 GO:6412 GO:3743 let-7a EPHA3 Hs.123642 3 Axon guidance 04360 GO:6468 GO:7165 GO:7169 00:5524 G0:5003 GO:l66 GO:5887 GO: 16020 32 200912002

GO:4674 GO:4713 GO:4872 GO:16740 let-7a EPHA4 Hs.371218 3 Calcium ion message path let-7a ERCC6 Hs.133444 3 DNA repair 73894 GO:6281 GO:6355 GO:7605 GO:6350 GO: 6366 GO:5524 GO:3677 GO:3678 GO:3702 00:4386 GO: 16787 GO:166 GO:5515 GO:5634 let-7a FARP1 Hs.567409 3 GO:7155 00:8092 GO:5085 GO:5737 GO: 5856 G0:16020 let-7a FBXL19 Hs.152149 3 GO:6508 GO:6355 GO:6512 GO:3677 GO:46872 00:5515 GO:4842 00:8270 GO:5737 let-7a FGF11 Hs.528468 3 let-7a FLJ21986 Hs.l 89652 3 let-7a FNDC3A Hs.508010 3 ECM-receptor interaction 04512 let-7a FRAS1 Hs.369448 3 let-7 a GALNT1 Hs.514806 3 Oxygen-linked glycan (O-Glycan) Biosynthesis 00512 GO :6493 GO:5509 GO:30145 GOA653 GO:5529 GO:16757 GO:5795 GO: 16021 let-7a GATM Hs.75335 3 Urea cycle and amine group metabolism; Glycine, serine and hydroxybutyric acid metabolism; Arginine and proline metabolism meta-7a GGA3 Hs.87726 3 GO:6886 GO:6461 G0:30306 GO:5515 GO:8565 GO:5795 GO:5802 G0:30130 33. 200912002

GO: 16020 let-7a GNAL Hs. 136295 3 About Ion Signal Conduction Path 04020 GO: 7186 GO: 7165 GO: 5525 GO: 3924 GO: 166 GO:4871 let-7a GNG5 Hs.554749 3 Energy Metabolism 163685 GO: 7186 GO :7165 GO:4871 GO:5834 let-7a GNPTAB Hs.46850 3 let-7a GRIK2 Hs.98262 3 Neuroactive Ligand-Receptor Interaction 04080 GO:7215 GO:6811 GO:6813 GO:7268 GO:68lO GO :5234 GO:5216 GO:4970 GO: 15277 GO;5267 GO:4872 GO:5215 GO:5887 GO: 16020 GO:45211 let-7a HAND1 Hs.152531 3 GO:7275 00:7507 GO:6355 GO:6366 G0 :3700 GO:5634 let-7a HAS2 Hs.159226 3 G0:50501 GO:16757 GO:5887 let-7a HDHD1A Hs.185910 3 GO:4 GO:8152 GO:3824 GO:5554 GO:8372 let-7a HECTD2 Hs .535293 3 GO:i5671 GO:6512 G0:20037 GO:5344 GO:4842 GO:5622 let-7a HIC2 Hs.517434 3 GO:45892 GO:6350 GO:3677 GO:46872 GO:8022 GO:8270 GO:5634 Let-7a HOMER2 Hs.459142 3 GO:7216 Iet-7a HOXA9 Hs.127428 3 GO:4 GO:7275 GO;6355 GO:5554 G0:3700 GO:16563 G0.5634 let-7a HOXB4 Hs.532669 3 GO: 7275 GO: 6355 G0: 3700 GO: 5634 34 200912002

Let-7a HOXD1 Ks.83465 3 GO:7275 GO:6355 G0:3700 GO:5634 let-7a HTR4 Hs.483773 3 Calcium ion signaling pathway 04020; Neurally active ligand-receptor interaction 04080 GO:7187 GO: 7165 GO:4935 GO:4872 GO:I584 GO:4993 GO-.5887 let-7a IL13 Hs.845 3 cytokine/cytokine receptor interaction 04060; Jak-STAT message path 04630 GO:19735) GO:6928 GO :8283 GO:7267 GO:6954 GO:7165 G0:8009 GO:5144 GO:4871 GO:5615 GO:5625 let-7a INPP5A Hs.523360 3 Inositol Hydrate Metabolism 00562; Phospholipid 醯 Inositol Message Transduction System 04070 GO:7154 GO:16787 GO:4437 GO:4445 GO: 16020 let-7a IRS2 Hs.442344 3 Adipocyte hormone signaling pathway 04920; insulin signaling pathway 04910; type 2 diabetes 04930; insulin receptor mediator signaling 74752 G0:6006 GO:8284 GO:7165 GO:5158 GO:4871 let-7a ITGB3 Hs.218040 3 ECM-receptor interaction 04512; focus attachment 04510; hematopoietic cell line age 04640; actin cytoskeleton regulation 04810; Hemostasis 109582 GO: 7596 GO:7155 GO:7160 GO:7275 GO:7229 GO:42802 GO:4872 GO:8305 let-7a KCNC2 Hs.2721 4 3 let-7a KIF1B Hs.97858 3 GO:8089 GO:9790 GO:7018 GO:7270 GO:7274 GO:5524 GO:16887 GO:19894 GO:8017 GO:3777 GO:166 GO:5515 GO:30659 GO :5874 GO:5875 GO:5739 let-7a KIF2 Hs.558351 3 GO:7018 GO:5524 GO:3777 GO: 166 GO:5856 GO:5874 GO;5875 35 200912002 let-7a KLF9 Hs.150557 3 Weekly Event GO: 6357 GO: 6350 GO: 46872 G0: 3700 GO: 8270 GO: 5634 let-7a KPNA4 Hs.288193 3 GO: 6607 GO:6886 GO: 5488 GO: 8565 GO: 5634 let-7a LOC2838 59 Hs.298434 3 Wnt message path 04310 let-7a LOC6431 76 Hs.403917 3 let-7a LOXL3 Hs.469045 3 let-7a LOXL4 Hs.306814 3 arginine and proline metabolism 00330 00:5507 GO:46872 GO:16491 GO :4720 GO:5044 GO: 16020 let-7a LRIG1 Hs.518055 3 let-7a LRIG2 Hs.448972 3 let-7a MAP3K7I P2 Hs.269775 3 MAPK message path 04010; Toll-like receptor signaling Path 04620 let-7a MED6 Hs.497353 3 MED6 〇〇:45944 GO:3702 GO:4872 GO:3713 GO:119 GO:5634 let-7a MEF2D Hs.314327 3 GO:7517 GO:6355 GO:6350 GO:6366 GO:3713 G0:3700 GO:5634 le T-7a MEIS2 Hs.510989 3 GO:122 GO:6355 GO:3704 GO:3714 G0:3700 GO:5634 let-7a MGAT4A Hs. 177576 3 Nitrogen-linked glycan (N-Glycan) Biosynthetic let-7a MTPN Hs .43297 3 let-7a MYCN Hs.25960 3 GO:6357 GO:5515 G0:3700 GO:785 GO:5634 36 200912002

Let-7a NAB1 Hs. 107474 3 GO:16481 GO:6355 GO:6350 GO:3676 GO: 16564 GO:5634 let-7a NCOA3 Hs.382168 3 GO:30521 GO:45893 GO:7165 GO.-8415 GO:50681 GO:4402 GO:5515 GO:4871 GO:46966 GO:3713 00:30528 GO:16740 GO:5634 let-7a NLK Hs.208759 3 Adhesive 〇4520;MAPK signal path 04010; Wnt message path 04310 GO: 30178 GO:6468 GO:7243 GO:6355 GO:5524 GO:4707 GO:287 GO:166 GO:5515 GO:4674 G0.4713 GO: 16740 GO:5634 let-7a NME4 Hs.9235 3 let-7a NPHP3 Hs .511991 3 let-7a NUMBL Hs.326953 3 Notch message path 05330 GO: 7399 let-7a NUP98 Hs.524750 3 GO.6260 GO: 6999 GO:6913GO:59 GO: 15031 GO:5515 GO:17056 GO:5215 GO:5643 GO:5654 let-7a OPRM1 Hs.2353 3 Neuroactive Ligand-Receptor Interaction 04080 GO:7186 GO:7187 GO:7610 GO:8285 G0:7600 GO:7165 GO:4988 GO:4872 GO: 1584 GO: 5794 GO: 5783 GO: 16021 G0.5887 GO'5886 let-7a P4HA2 Hs.519568 3 Arginine and proline metabolism 00330 GO: 19538 GO: 31418 GO: 5489 GO: 5506 GO: 46872 GO: 5783 • 37 200912002

GO: 16491 GO: 16706 GO: 16702 GO: 4656 GO: 5515 let-7a ΡΑΚΙ Hs.435714 3 Axon guidance 04360; focus attachment 04510; MAPK signal path 04010; natural killer cell cytotoxicity 04650; Regulation of protein cytoskeleton 04810; Τ cell receptor signaling pathway 04660 GO: 7254 GO: 6915 GO; 6468 GO: 5524 GO: 166 GO; 5515 GO: 4674 GO: 4713 GO: 16740 let-7a PANX2 Hs.440092 3 GO:5921 GO:16021 let,7a PAPPA Hs.494928 3 GO:30154 GO:7565 GO:6508 GO:46872 GO:8237 GO:8270 GO:5615 GO: 16020 let-7a PAX3 Hs.42146 3 GO:6915 GO :7275 GO:7399 GO:9887 GO:6355 GO:7605 GO:6366 G0:3700 GO:5634 let-7a PBX2 Hs.509545 3 GO:7387 GO:7388 GO:6355 GO:5515 G0:3700 GO:5634 let -7a PDGFB Hs.1976 3 cytokine-cytokine receptor interaction 04060; focus attachment 04510; gap junction 04540; ΜΑΡΚ message transduction pathway 04010; actin cytoskeleton regulation 04810; hemostasis 109582 GO:8283 GO:74 GO: 9611 GO:8083 GO:5161 GO:5576 GO: 16020 let-7a PHF8 Hs.133352 3 GO:6355 GO:46872 GO:5515 38 200912002

GO:8270 let-7a PLAGL2 Hs.154104 3 GO:6355 00:6350 GO:46872 G0.3700 GO:8270 GO:5634 let-7a PLCB4 Hs.472101 3 Calcium ion signal path 04020; gap junction 04540; inositol Phosphate metabolism 00562; phospholipid inositol signaling system 04070; Wnt message path 05310 GO: 7242 GO: 16042 GO: 6629 GO: 5509 GO: 16787 GO: 4435 GO: 4871 let-7a PLD3 Hs.257008 3 GO: 8152 GO:3824 let-7a PLEKHG 6 Hs.163953 3 GO:5085 let-7a PLEKHO 1 Hs.438824 3 let-7a PLGLB2 Hs.528525 3 let-7a POGZ Hs.489873 3 GO:7275 00:3677 GO:46872 GO :3676 GO:8270 GO:5634 let-7a POLH Hs.439153 3 let-7a PPARGC1 A Hs.527078 3 Adipocyte hormone signaling pathway 04920; insulin signaling pathway 04910 GO:8380 GO:30521 GO:50873 GO:1678 GO:45333 00:7586 GO:19395 00:6094 GO:6397 G0:7005 GO:46321 GO:45722 GO:35066 GO:45893 GO:6461 GO:50821 GO:3677 GO:3723 GO:16455 GO:50681 GO: 30374 GO: 166 GO: 8134 GO: 5665 GO: 5634 39 200912002

GO: 42594 GO: 1659 GO: 6350 GO: 6367 let-7a PPP3CA Hs.435512 3 amyotrophic atherosclerosis 05030; apoptosis 04210; axon guidance 04360; B cell receptor signaling pathway 04626; calcium Ion message transduction path 04020; MAPK message transduction path 04010; natural killer cell vector cytotoxicity 04650; T cell receptor message transduction path 04660; Wnt message path 05310 GO: 6470 GO: 5509 GO: 5516 GO: 16787 GO: 5506 GO:4722 GO:8270 GO:5955 GO:5634 let-7a PRDM2 Hs.371823 3 GO:6355 GO:46872 GO:3676 G0:3700 GO:8270 00:5634 let-7a PRRX1 Hs.283416 3 let-7a PTPRU Hs.19718 3 GO:7155 GO:6470 GO:7185 GO:16787 GO:4725 GO:4872 G0:5001 GO:5887 GO: 16020 let-7a PYG02 Hs.433795 3 let-7a QARS Hs.79322 3 Amino acid Mercapto-tRNA synthetase 00970; glutamic acid metabolism 00251 GO: 6425 GO: 6424 GO: 6412 GO: 5524 GO: 4818 GO: 4819 GO: 16874 GO: 166 GO: 5515 GO: 5737 GO: 5625 let-7a RAI16 Hs.491223 3 let-7a RAPGEF6 Hs.483329 3 let-7a RASL10B Hs.437035 3 let-7a RBI Hs.408528 3 Cell cycle 04110; cell cycle 69278 GO:3 0521 GO:75 GO:50681 GO:5554 GO:785 GO:5634 40 200912002 GO:45786 GO:6469 GO: 122 GO:45893 GO:6355 GO:6350 GO:5515 GO:3713 G0:3700 let-7a RBM9 Hs .282998 3 ribosomal protein let-7a RDH10 Hs.244940 3 let-7a RDX Hs.263671 3 regulation of actin cytoskeleton 04810 GO:51016 GO:7016 GO:3779 GO:5488 GO:5198 GO:15629 GO: 5737 GO: 5886 let-7a RGAG1 Hs.201071 3 let-7a RNF20 Hs.168095 3 GO: 16567 GO: 46872 GO:4842 GO:8270 GO:151 let-7a RNF38 Hs.333503 3 GO:16567 GO:46872 GO ;4842 GO:8270 GO:151 let-7a RNF44 Hs.434888 3 GO:16567 ^0:46872 GO:4842 GO:8270 GO:151 let_7a RNF5 Hs.534342 3 GO; 16567 GO:46872 00:5515 GO:4842 GO:8270 GO:151 let-7a RUFY3 Hs.7972 3 let-7a SCN5A Hs.556087 3 GO:6812 GO:6936 GO:8016 GO:6814 GO:5261 GO:31402 GO:5248 GO: 16021 GO: 16020 GO :5624 GO:1518 let-7a SCUBE3 Hs.12923 3 let-7a SEC24C Hs.81964 3 GO:6888 GO:6886 GO:3779 GO:5554 GO:5515 GO:30127 GO:5795 GO:5783 let-7a SEMA3F Hs .32981 3 Axon guidance 04360 00:7275 00:5615 let-7a SEMA4G Hs.5 67556 3 Axon guidance 04360 GO: 30154 GO: 4872 GO: 16021 41 200912002

GO:7399 GO: 16020 let-7a SENP2 Hs.401388 3 Wnt message path GO:6508 GO:16929 GO:5643 04310 00:30111 GO:8234 GO:5634 GO:6512 GO:5515 Iet-7a SENP5 Hs.533124 3 let-7a SFRS12 Hs.519347 3 mRNA synthesis regulation let-7a SLC25A1 Hs.282982 3 GO:6810 GO:5488 GO:16021 8 GO:15293 GO:5743 GO:5739 let-7a SLC25A1 Hs.570482 3 GO:6810 GO: 5488 GO: 16021 8 GO: 15293 GO: 5743 GO; 5739 let-7a SLC25A4 Hs.246506 3 Calcium ion signaling path GO: 6091 GO: 2 GO: 15207 GO: 16021 04020; Nucleotide metabolism GO: 6839 GO:5488 GO:5887 15869 GO:6810 GO:5215 GO: 16020 GO:5743 GO:5739 let-7a SLC4A4 Hs.5462 3 GO:6820 GO:5452 GO:16021 GO:6810 GO:8510 GO:5887 G0: 16020 let-7a SLC6A1 Hs.443874 3 let-7a SLC6A15 Ks.44424 3 GO:6836 GO:5328 00:5887 GO:15293 G0:16020 let-7a SLC05A1 Hs.443609 3 GO:6810 GO:5215 GO:16021 G0 :16020 let-7a SMARCA Hs.410406 3 D1 let-7a SMARCC Hs.476179 3 GO:6333 GO:3677 GO:16514 1 GO:6338 GO:3682 GO:785 GO:45893 GO:5515 GO:5654 G〇;45449 GO:3713 00:5634 GO:6357 let-7a SPATA2 Hs.48513 3 GO:30154 GO:5554 GO:5737 00 :7283 let-7a STARD13 Hs.507704 3 let-7a STRBP Hs.287659 3 42 200912002

Let-7a SYT1 Hs.310545 3 let-7a TAF5 Ks.96103 3 RNA Transcription Iet-7a TARBP2 Hs.326 3 GO:6469 GO:45946 00:45070 GO:6357 GO:46782 GO:3725 GO:46982 GO:5622 GO: 5634 let-7a TBX5 Hs.381715 3 GO: 7507 GO: 9653 GO: 45893 GO: 6355 GO: 6350 GO: 3702 GO: 5515 G0: 3700 GO: 5634 let-7a TGFBR1 Hs.494622 3 Adhesive bonding 04520; Cytokine-cytokine receptor interaction 04060; MAPK signaling pathway 04010; TGF-beta signaling pathway 04350 GO: 6468 GO: 7165 GO: 7181 GO: 7178 GO: 5524 GO: 287 GO: 30145 GO: 166 GO: 4713 GO;4872 GO:16740 GO:5024 GO:5025 GO:16021 GO:5887 G0:16020 let-7a TIMM17B Hs.30570 3 GO:6626 GO:15450 GO:16021 GO:5744 GO:5739 let-7a Transcribe d locus Hs.408973 3 let-7a Transcribe d locus Hs.560163 3 let-7a TRIB2 Hs.467751 3 GO:6468 GO:43405 GO:5524 GO:166 GO:4674 GO:4713 GOA6740 GO:5737 let-7a TRIM41 Hs. 441488 3 let-7a TSC22D2 Hs.52526 3 GO:6355 G0:3700 let-7a TTLL4 Hs.471405 3 GO:6464 GO: 16874 00:4835 43 200912002

Let-7a ULK2 Hs. 168762 3 GO:6468 GO:5524 GO:166 GO:4674 GO:4713 GO: 16740 let-7a USP25 Hs.473370 3 GO:6508 GO:6512 GO:6511 GO:4197 GO:4221 let -7a VAV3 Hs.267659 3 B cell receptor signaling pathway 04462; focal attachment 05510; cytotoxicity of natural killer cell media 04650; regulation of actin cytoskeleton 04810 GO: 7242 GO: 7264 GO: 5096 G0:5070 GO : 19992 00:5085 GO:46872 GO:8270 let-7a VSNL1 Hs.444212 3 GO:5509 let-7a WDFY3 Hs.480116 3 let-7a WNT1 Hs.248164 3 Hedgehog message path 04340; Wnt message path 04310 GO :30154 GO: 1708 GO: 16477 GO:7417 GO:7163 GO:7223 GO:9653 GO:7283 GO:5102 GO:5576 GO:5625 let,7a XKR8 Hs.55024 3 GO:16021 let-7a ZC3H3 Hs.521915 3 GO: 46872 GO: 3676 GO: 8270 let-7a ZCCHC5 Hs. 134873 3 GO: 46872 GO: 3676 GO: 8270 let-7a ZFYVE26 Hs.98041 3 GO: 3676 GO: 8270 GO: 5634 let-7a ZNF318 Hs. 509718 3 GO:3824 GO:3676 GO:3735 GO:8270 GO:5634 44 200912002 let-7a ZNF644 Hs. 173001 3 GO-6355 GO:6350 GO:3677 GO:46872 GO:8270 GO:5634 let-7a ZZ Z3 Hs.480506 3 GO:45449 GO:3677 GO:8270 GO:5634 miR-182* DOCK9 Hs.314413 4 miR-182* AARS Hs.315137 3 Alanine and asparagine metabolism 00252; Amino guanidine BASE-tRNA synthetase 00970 GO:6419 GO:6412 GO:8033 GO:5524 GO:4813 GO:16874 GO:3676 GO:166 GO:49 GO:5737 GO:5625 miR-182* ABCG1 Hs.124649 3 ABC Round protein general type 02010 GO:42632 GO.8203 GO:9720 GO:6869 G0:10033 GO:5524 GO: 16887 GO:42626 GO:15196 GO:166 GO:15646 GO:46983 GO:15216 (30:5795 GO: 5783 GO: 5887 G0: 16020 GO: 5624 miR-182* ALDH18 A1 Hs. 500645 3 Urea cycle and amine group metabolism 00220 GO: 8652 GO: 8152 GO: 6561 GO: 3942 GO: 4349 GO: 4350 GO: 16301 GO: 16491 GO:16740 GO:5739 GO: 19866 miR-182* BACH2 Hs.269764 3 GO:6355 <30:6350 GO:3677 GO:5515 GO:5634 miR-182* CBX3 Hs.381189 3 Weekly activity GO :6333 GO: 16568 GO:6355 GO:6350 GO:3682 GO:5515 GO:785 GO:5634 miR-182* CD36 Hs.120949 3 Adipocyte Hormone Signaling Path 04920; ECM-Receptor Interaction 04512; Hematopoietic Cell Line Age 04640; Hemostasis 109582 GO: 7596 GO: 7155 GO: 6631 GO: 6629 GO :6810 GO:5515 GO:4872 GO:5887 GO: 16020 GO:5624 miR-182* CRLF1 Hs.114948 3 GO.19735+F280 GO: 19955 GO:5615 45 200912002

GO:4872 miR-182* CXXC5 Hs.189119 3 GO:3677 GO:8270 miR-182* FAT Hs.481371 3 GO:7155 GO:7267 GO:7156 GO:9653 GO:5509 GO:5515 GO:5887 GO: 16020 miR-182* FBXW11 Hs.484138 3 Hedgehog message transduction path 04340; Ubiquitin medium protein hydrolysis 04120; Wnt message path 04310 GO: 16055 GO: 16567 GO:4842 GO:151 miR-182* FYCOl Hs .200227 3 miR-182* KCMF1 Hs.345694 3 miR-182* GALNT1 Hs.514806 3 Oxygen-linked glycan (O-Glycan) Biosynthesis 00512 GO: 6493 GO: 5509 GO: 30145 GO: 4653 GO: 5529 GO: 16757 GO: 5795 GO: 16021 miR-182* HDAC7A Hs. 200063 3 Cell cycle 04110 GO: 30183 GO: 16568 GO: 6954 GO: 45843 GO: 7399 GO: 74 GO: 6355 GO: 6350 GO: 4407 GO: 16787 GO :16566 GO:8134 GO:5737 GO:118 GO:5634 miR-182* HDHD2 Hs.465041 3 miR-182* HOXB4 Hs.532669 3 GO:7275 GO:6355 G0:3700 GO:5634 miR-182* HRMT1L 4 Hs.504530 3 Amino-based lipid metabolism 00440; androgen and emodin metabolism 00150; histidine metabolism 00340; nitrobenzene degradation 00626; selenoic acid metabolism 00450; tryptophan metabolism 00380; tyrosine metabolism GO: 8757 GO: 16740 GO: 5634 46 200912002

00350 miR-182* ITGA10 Hs.158237 3 ECM-Receptor Interaction 04512; GO:7155 GO.5509 GO:16021 Focus Attachment 04510; Actin GO:7160 GO:5518 GO:8305 Regulation of Protein Cytoskeleton GO:7229 GO :287 04810 GO:4872 miR-182* LGI1 Hs.533670 3 GO:8283 GO:7399 miR-182* MAPK9 Hs.484371 3 Adipocyte Hormone Signaling GO:7254 GO:5524 Path 04920; Focus Attached GO:6468 GO :4705 04510; Insulin message transmission GO.-6950 GO: 4707 path 04910; MAPK message GO: 166 interest transmission path 04010; class GO: 5515 铎 (Toll-like) receptor message GO: 4674 interest conduction path 04620; :4713 Type 2 Diabetes 04930; Wnt Signal Path 04310 GO:16740 miR-182* PLA2G6 Hs.170479 3 Glycerophospholipid Generation GO:16042 GO:16787 GO:5737 Xie 00564; MAPK Signal Path 04010; Prostaglandins and Leukotriene Metabolism 00590 GO:6644 GO:4623 G0:16020 miR-182* PLAGL2 Hs.154104 3 GO:6355 GO:46872 GO:5634 GO:6350 G0:3700 GO:8270 miR-182* PLCL2 Hs.202010 3 miR-182 * RAB5A Hs.475663 3 GO:6897 G〇:5525 GO:5769 GO:6886 GO:3924 GO:7264 GO: 166 GO:5515 miR-182* RAB6A Hs.503222 3 G0.6888 GO:5525 GO:5795 GO:15031 GO:3924 GO:7264 GO:166 GO:5515 miR-182* RBM12 Hs.246413 3 miR-182* RPS6KA1 Hs. 149957 3 ribosomal protein; calcium ion GO:6468 GO:5524 message transduction pathway; phospholipid 醯GO: 7165 GO: 166 Inositol Message Transduction System GO: 4672 47 200912002

GO:4674 GO:4713 GO-.3735 GO:16740 miR-182* SBF1 Ks.449098 3 GO:46839 GO:4437 GO: 16021 GO:6470 GO:813S GO:5634 miR-182* SLC18A1 Hs. 158322 3 GO :15893 GO:15238 GO:16021 GO:15844 GO:8504 GO:5624 GO: 15293 miR-182* SMAD7 Hs.465087 3 TGF-beta message path GO:6355 GO:5515 GO:5634 04350 GO:6950 GO: 5076 GO:6350 GO:30617 GO:7179 miR-182* TACR3 Hs.942 3 Calcium ion signal path GO:7165 GO:4872 GO:5887 04020; Neurally active ligand 'receptor interaction 04080 ----- --- GO:7217 GO:1584 GO:5886 miR-182* TCERG1 Hs.443465 GO:4995 3 GO:6355 GO:3702 GO:5634 GO:6350 GO:6366 GO:5515 GO:3713 miR-182* TFiPll Hs_2〇225 3 GO:30154 GO:3676 GO:5634 GO:30198 GO:5515 GO: 1503 miR-182* TP53INP2 Hs.516994 ----- --_ '--------- GO: 45045 miR-182* UBE2B Hs.385986 Ubiquitin Media GO:6281 GO: 16874 G0:16020 Protein Hydrolysis; GO:6512 GO:8642 GO:5634 miR-182* VAT1 Hs.514199 —— -~ GO:4842 0 GO:16049 GO:3677 GO:16021 GO:16491 GO:5634 miR-182* ZFP36L2 Hs.503093 3 '-- GO:8270 GO:8021 GO:8283 GO:46872 GO:5634 GO: 3676 G0:3700 miR-182* ZIC3 Hs. 111227 ο GO:8270 GO:7368 GO;3677 GO:5634 GO:6355 GO:46872 L---- GO:6350 GO: 8270 48 200912002

miR-372 ATXN1 Hs.434961 4 GO:3723 GO:5737 GO:5634 miR-372 POLH Hs.439153 4 miR-372 BCL11B Hs.510396 4 GO:6355 GO:6350 GO:46872 GO:3676 GO:8270 GO: 5634 miR-372 DPYSL5 Hs.299315 4 Axon guidance 04360 GO:7411 GO:7399 GO:7165 GO:16787 miR-372 ΪΝΗΒΒ Hs.1735 4 cytokine-cytokine receptor interaction 04060; TGF-beta message transduction pathway 04350 GO:30154 GO:6952 G0:40007 GO:46882 GO:48178 GO:1541 GO:5125 GO:8083 GO:5179 GO:46789 GO:42803 GO:5576 miR-372 MAP3K11 Hs.502872 4 Calcium ion conduction path GO:80 GO:7257 GO:8283 GO:7017 GO:46777 GO:51259 GO:5524 GO:4706 GO:166 GO:5515 GO:42803 GO:4674 GO:4713 GO:5813 GO:5874 miR-372 MYCN Hs .25960 4 GO:6357 GO:5515 G0:3700 GO:785 GO:5634 miR-372 NEUROD 6 Ks.45152 4 GO:6355 GO:3677 00:30528 GO:5634 miR-372 NFIB Hs.370359 4 GO:6260 GO:6355 GO:6350 G0:3700 GO:5634 miR-372 PARP8 Hs.369581 4 miR-372 CDNA FLJ38785 fis Hs.406990 4 miR-372 RBBP7 Hs.495755 4 GO:8283 GO:7275 GO:5515 GO:5634 miR-372 SS18L1 Hs. 154429 4 GO:5515 49 2 00912002

miR-372 TLE4 Hs.444213 4 GO:4 GO:7222 GO:6355 GO:5554 GO:5634 miR-372 ADAM9 Hs.2442 3 GO:7243 GO:6508 GO:17124 GO:5178 GO:46872 GO:4222 GO :5515 GO:19901 GO:8270 GO:5887 miR-372 AEBP2 Hs.126497 3 miR-372 AMPD2 Hs.82927 3 Metabolic miR-372 ANK2 Hs.567235 3 Ribosomal protein miR-372 APBB2 Hs.479602 3 G0: 30048 GO:7409 G0:7050 GO:7242 GO:45749 G0:30308 GO:50821 GO:1540 GO:35035 GO:8134 GO:30426 G0:30027 GO: 16020 GO:5634 GO:45202 miR-372 APP Ms.434980 3 Alzheimer's disease 05010; neurodegenerative disease 01510; hemostasis 109582 GO: 7219 GO: 6915 GO:7155 GO:6878 GO:6897 G0:50905 GO:5507 GO:8201 GO:5506 GO:46872 GO:5515 GO :4867 GO:8270 GO:9986 GO:5905 GO:5576 GO:5887 miR-372 ARHGAP 9 Hs.437126 3 GO:5096 miR-372 ARHGEF 10 Hs.98594 3 miR-372 ARID4A Hs. 161000 3 GO:6333 GO :45892 GO:6350 GO:6366 GO:3682 GO:5515 G0:3700 GO:16564 GO:785 GO:5634 GO:17053 miR-372 ARID4B Hs.533633 3 —^ 3 --—J ------ ----- --- GO:3677 GO:3676 GO:5622 miR-372 ATP2B2 Hs.268942 GO:6816 GO:5524 GO:16021 ----------1 50 200912002

miR-372 ATP2B4 Hs.343522 — ---_ r——^ 04020 二^^_ GO:6812 GO:8152 GO:5509 GO:5388 GO:5516 GO:16787 GO: 16820 GO:5886 Qiao ion message conduction path 04020 GO:6816 GO:6812 GO:8152 GO:5524 GO:5509 GO:5388 GO:5516 GO:16787 GO: 16820 GO:5887 GO:5886 miR-372 BAHD1 Hs.22109 3 — 3 miR-372 BCL11A Hs. 370549 G0:30097 GO:6355 GO:6350 GO:46872 GO:3676 GO:8270 GO:5737 GO:5634 miR-372 BRP44L Hs.172755 3 GO:5554 miR-372 BTG1 Hs.255935 3 Sunday Activity GO: 16477 G0:30308 GO:8285 GO:45766 GO:45603 GO:43085 G0:19900 GO:3712 GO:5737 GO:5634 miR-372 C15orfl7 Hs.367690 3 miR-372 C16orf28 Hs643536 3 GO: 16567 GO:4842 GO: 8270 GO: 151 miR-372 CCND2 Hs.376071 3 Cell cycle 04110; focus attachment 04510; Jak-STAT message path 04630; Wnt message path 04310; cell cycle 69278 GO: 51301 GO: 74 GO: 5634 miR-372 CDC2L6 Hs.159118 3 miR-372 CFL2 Hs.180141 3 G13 message transduction pathway miR-372 COL23A1 Hs.413494 3 miR-372 TNXB Hs.42853 3 G1 to S cell cycle; smooth hunger contraction miR-372 CRIM1 Hs.332847 3 51 200912002

miR-372 CUL4A Hs.339735 3 miR-372 DAZAP2 Hs.369761 3 Weekly activity miR-372 DMTF1 Hs.558441 3 miR-372 E2F5 Hs.445758 3 Cell cycle 04110; TGF-beta message pathway 04350; cell cycle 69278 GO:74 GO:6355 GO:6350 GO:5515 G0:3700 GO:5634 GO:5667 miR-372 EIF2C1 Hs.22867 3 GO:6412 GO:6446 GO:5515 00:3743 GO:5850 miR-372 EPAS1 Hs .468410 3 GO: 1525 GO:30154 GO:6355 GO:1666 GO:7165 GO:6366 GO:3705 GO:35035 GO:5515 GO:4871 GO:3713 GO:5634 miR-372 EPHA2 Hs.171596 3 Axial guidance引04360 GO:7275 GO:6468 GO:7165 GO:7169 GO:5524 G0:5003 GO:166 GO:4674 GO:4872 GO: 16740 GO:5887 G0.16020 miR-372 ERBB4 Hs.390729 3 Calcium ion signal conduction Path G4〇20; back-to-back axis formation 04320 GO:8283 GO:7275 GO:6468 GO:7169 GO:5524 G0:5006 GO:166 GO:5515 GO:4872 GO:16740 GO:5887 GO: 16020 miR-372 FBXL11 Hs. 124147 3 GO:6355 GO:6512 GO:3677 GO:46872 GO:5515 00:8270 miR-372 Transcribe d locus Hs.246781 3 miR-372 miR-372 FNDC3A GCAT Hs.508010 Hs.54609 3 —-- — 3 1----- Body Interaction 04512 Glycine , Serine and alanine metabolism in hydroxybutyrate 00260 --- GO: 6520 GO: 9058 GO: 8415 GO: 8890 GO: 16874 GO: 16769 GO: 5739 52 200912002

miR-372 GPR161 Hs.271809 3 GPCRDBA-type rhodopsin 2 miR-372 GPR6 Hs.46332 3 GPCRDBA-type rhodopsin GO:7186 GO:7165 GO:16526 GO:4872 GO:1584 GO:5887 miR-372 HBP1 Hs.162032 3 GO: 16055 GO:6355 GO:6350 GO:3677 GO:5634 miR-372 HIC2 Hs.517434 3 GO:45892 00:6350 GO:3677 GO:46872 GO:8022 GO:8270 GO:5634 miR -372 HNRPH3 Hs.198158 3 miR-372 IRF2 Hs.374097 3 Apoptosis GO:8283 GO:6955 GO: 122 GO:6355 GO:6350 GO:3702 G0:3700 GO:5634 miR-372 KCNMA1 Hs.568865 3 miR-372 KIF3B Hs.369670 3 miR-372 KLF12 Hs.373857 3 GO:6357 00:6350 GO:46872 GO:3714 G0:3700 GO:8270 GO:5634 miR-372 LATS2 Hs.78960 3 GO:82 GO: 7049 GO:51301 GO:9755 GO:7067 GO:45736 GO:6468 GO:5524 GO:287 GO:166 GO:4674 GO:4713 GO: 16740 GO:5634 GO:922 miR-372 LOC6415 18 Hs.535760 3 TGF Beta message path miR-372 LEF1 Hs.555947 3 Adhesive bonding 04520; Wnt message path 04310 GO: 16055 GO: 6355 GO: 6350 GO: 3677 GO: 5634 miR-372 LHX6 Hs.103137 3 GO: 7420 GO: 6355 GO: 46872 G0: 3700 GO: 5634 53 200912002

GO:8270 miR-372 LUC7L2 Hs.530118 3 GO:46872 GO:8270 miR-372 MBNL2 Hs.125715 3 miR-372 MEF2C Hs.444409 3 MAPK message path 04010 GO:7517 GO:7399 GO:6355 GO:6350 GO:6366 GO:3702 GO:3713 G0:3700 GO:5634 miR-372 MKRN1 Hs.490347 3 GOA GO: 16567 GO:46872 GO:5554 GO:3676 GO:5515 GO:4842 GO:8270 GO:8372 GO: 151 miR-372 MTMR3 Hs.474536 3 GO:46839 GO:6470 GO:16787 GO:4437 GO:46872 GO:4722 00:4725 GO:8270 GO:5737 GO:5624 miR-372 NEK9 Hs.7200 3 GO:7049 GO:51301 GO:7067 GO:6468 GO:5524 GO:287 GO:166 GO:4674 GO: 16740 miR-372 NEUROD 1 Hs.72981 3 GO:30154 GO:7399 00:6355 GO:3677 GO:3702 GO: 5634 miR-372 NPAS3 Hs.509113 3 GO:6355 GO:7165 GO:3677 GO:4871 GO:30528 GO:5634 miR-372 NR4A2 Hs. 165258 3 Nuclear Receptor GO:19735) GO:6355 GO:7165 GO: 6350 GO: 4879 GO: 46872 GO: 3707 G0: 3700 GO: 8270 00: 5634 miR-372 NR4A3 Hs. 279522 3 Hypertrophy GO: 4 GO: 6355 GO: 5488 GO: 5634 54 200912002

Model) GO:6350 GO:4879 GO:46872 GO:3707 GO:4887 G0:3700 GO:8270 miR-372 OSBPL8 Hs.430849 3 GO:6869 GO.8202 miR-372 PAPOLA Hs.253726 3 mRNA synthesis regulation miR- 372 PCAF Hs.533055 3 miR-372 PCDHA4 Hs.199343 3 miR-372 PERQ1 Hs.414396 3 miR-372 PHF1 Hs.166204 3 GO:6355 GO:46872 GO:3676 GO:5515 GO:37 (8) GO:8270 GO :5634 miR-372 PHF2 Hs.211441 3 GO:6355 GO:46872 GO:5515 G0:3700 GO:8270 GO:5634 miR-372 PLAG1 Hs.14968 3 GO:46872 GO:3676 G0:3700 GO:8270 GO: 5634 miR-372 PLAGL2 Hs.154104 3 GO:6355 GO:6350 GO:46872 G0:3700 GO:8270 GO:5634 miR-372 POLK Hs.135756 3 DNA polymerase 03030 GO:6281 GO:6260 GO:6280 GO: 3677 GO: 3887 GO: 287 GO: 16740 GO: 8270 GO: 5634 miR-372 POLQ Hs.241517 3 嘌呤 metabolism; pyrimidine metabolism; DNA polymerase miR-372 PPP3CA Hs.435512 3 amyotrophic atherosclerosis 05030; Apoptosis GO: 6470 GO: 5509 GO: 5516 GO: 5955 GO: 5634 55 200912002 04210; axon guidance 04460; B cell receptor signaling pathway 04462; calcium ion signaling pathway 04020; MAPK signaling Trail GO: 16787 GO: 5506 GO: 4722 GO: 8270 miR-372 PPP3CA Hs.535457 3 G protein signaling; calcium ion signaling pathway miR-372 PPP6C Hs.495128 3 GO: 82 GO: 6470 GO: 16787 GO: 5506 GO:30145 GO:46872 GO:4722 miR-372 PRDM4 Hs.506655 3 GO:8283 GO:6355 GO:7165 GO:6350 GO:6366 GO:3677 GO:3702 GO:46872 GO:8270 GO:5634 miR- 372 PRRX1 Ks.283416 3 miR-372 PUM1 Hs.144795 3 GO:6812 GO:6936 GO:7269 GO:6813 GO:7268 GO:5509 GO: 15269 GO:287 GO:30955 GO:5515 GO:5249 GO: 16021 GO: 16020 GO: 8076 miR-372 RAB11A Hs.321541 3 miR-372 RAB6A Hs.503222 3 GO:6888 GO:15031 GO:7264 GO:5525 GO:3924 GO:166 GO:5515 GO:5795 miR-372 RAB6C Hs.535586 3 GO:6886 GO:42493 GO:7264 GO:5525 GO:3924 GO: 166 GO:5622 miR-372 RAB7 Hs.15738 3 GO:6897 GO:6886 GO:7264 miR-372 RAB7B Hs.534612 3 GO:6886 GO:5525 GO:5764 56 200912002

GO: 7264 GO: 166 miR-372 RABGAP 1 Hs.271341 3 miR-372 RALGDS Hs.106185 3 GO: 7264 GO: 5085 GO: 8372 miR-372 RBL2 Hs.513609 3 Cell cycle 04110; TGF-beta message transduction pathway 04350 GO:7049 GO:45786 GO:6355 GO:6350 GO:3677 GO:5515 GO:5634 miR-372 RBM17 Hs.498548 3 mRNA synthesis regulation miR-372 RDBP Hs.423935 3 Gene expression 74160; Transcription 74159 GO:4 GO:6355 GO:6350 GO:3723 GO:166 GO:5515 GO:5634 miR-372 RGL1 Hs.497148 3 GO:7264 GO:8321 GO:5515 GO:8372 miR-372 RHOC Hs.514941 3 miR-372 RPS6KA1 Hs.149957 3 ribosomal protein; calcium ion signaling pathway; phospholipid lysis protein signaling system GO: 6468 GO: 7165 GO: 5524 GO: 166 GO: 4672 GO: 4674 GO: 4713 GO: 3735 GO: 16740 miR- 372 RPS6KA5 Hs.510225 3 MAPK message path 04010 GO:7173 GO: 16572 GO:6468 GO:7243 GO:6508 GO:6355 GO:422 GO:5524 GO:3824 GO:8237 GO: 166 GO:5515 GO:4674 GO:4713 GO:16740 GO:5634 miR-372 RSBN1 Hs.486285 3 miR-372 RTNl Hs.368626 3 GO:30182 GO:7165 GO:5554 GO:4871 GO:5783 GO:30176 GO:16021 miR-372 RUNX1 Hs. 149261 3 GO:7275 GO:45944 GO:6355 GO:5524 GO:5515 G0:3700 GO:5634 57 200912002

GO:6350 GO: 16563 miR-372 SAR1B Hs.432984 3 GO:6888 GO:5525 GO:5795 GO:6886 GO:287 GO:166 GO:5783 GO:7264 GO: 16020 miR-372 SART1 Hs.502883 3 GO :5829 miR-372 SENP1 Hs.371957 3 GO:6508 GO:8234 GO:5634 GO:6512 GO:4175 miR-372 SLC2A4 Hs.380691 3 Adipocyte Hormone Signaling GO:5975 GO:5355 GO:9897 Path 04920; Insulin News GO:8643 GO:5515 GO:5887 Interest conduction path 04910; GO:42593 GO:5351 G0:16020 Type 2 diabetes 04930; Sugar GO: 15758 GO:5215 GO:5624 Metabolism 71387 GO:48471 GO: 12506 miR-372 SLITRK3 Hs.101745 3 GO:16021 miR-372 STAT3 Hs.463059 3 Adipocyte Hormone Signaling GO:7259 GO:5509 GO:5737 Path 04920; Jak-STAT GO:6953 GO:5062 GO:5634 Message Conduction Path 04630 GO: 6928 GO: 4871 GO: 19221 G0: 3700 GO: 7242 GO: 8134 GO: 122 miR-372 SUV39H1 Hs.522639 3 Degradation of amino acid 00310 GO: 67 GO: 6333 GO: 8757 . GO: 785 GO : 16568 GO:3682 GO:794 GO:46974 GO:5634 GO: 18024 GO:5515 GO: 167 miR-372 SUV420H 1 Hs.503001 3 miR-372 TIPARP Hs.12813 3 miR-372 TP53INP2 Hs.516994 3 miR-372 TRPS1 Hs.253594 3 GO:6607 GO:46872 GO:5634 GO:6355 G0: 3700 GO: 1501 GO: 8270 GO: 6350 GO: 6366 miR-372 TRPV6 Hs.302740 3 58 200912002

miR-372 TUSC2 Hs.517981 3 3 ---3 miR-372 miR-372 UBE2B VLDLR Hs.385986 Hs.370422 Protein hydrolysis in Ubiquitin Media GO:6281 GO:6512 GO:16874 GO:8642 GO: 4842 G0:16020 GO:5634 GO:8203 GO:6897 GO:6629 GO:6869 GO:7613 GO:7399 GO:7165 GO:8202 GO:5509 GO:5319 GO:5041 GO:4872 GO:5905 GO:16021 G0 :16020 GO:5624 miR-372 YWHAZ Hs.492407 3 Cell cycle 04110 GO: 19904 miR-372 ZBTB4 Hs.35096 3 miR-372 ZDHHC1 7 Hs.4014 3 GO:42953 GO:43123 GO:8415 GO:46872 GO: 5515 GO:19706 GO:4871 GO:16740 GO:8270 GO:5795 GO: 16021 G0:16020 miR-372 ZNF238 Hs.69997 3 GO:7001) GO:122 GO:6355 GO:6350 GO:6810 GO:46872 GO :3676 GO:5515 GO:3704 GO:37 (8) GO:8270 GO:228 GO:5634 miR-372 ZNF385 Hs.505653 3 miR-372 ZNF532 Hs.529023 3 GO:3677 GO:46872 GO:8270 GO:5634 miR -372 PRDM8 Hs.373642 3 GO:6355 GO:6350 GO:3677 GO:46872 GO:3676 00:8270 GO:5634 miR-372 DDOST Hs.523145 3 Nitrogen-linked glycan (N-Glycar® biosynthesis 00510 GO: 18279 GO: 4579 GO: 16740 GO: 5789 GO: 16021 59 200912002

miR-372 ZFP91 Hs.524920 3 miR-372 FBXL4 Hs.536850 3 GO:6512 GO:6511 GO:5634 GO:151 miR-221 PHF1 Hs. 166204 5 GO:6355 GO:46872 GO:3676 GO:5515 G0: 3700 GO: 8270 GO: 5634 miR-221 PHF2 Hs.211441 5 GO: 6355 GO: 46872 GO: 5515 G0: 3700 GO: 8270 GO: 5634 miR-221 ATP1A4 Hs.367953 5 Calcium ion regulation in heart cells GO: 15991 GO:6812 GO:30641 GO:8152 GO:6813 GO:6814 GO:30317 GO:5524 GO: 15662 GO:3824 GO:16787 GO:16820 GO:287 GO: 15077 GO:166 GO:30955 GO:31402 GO :5391 GO: 16020 GO:5890 miR-221 ZNF385 Hs.505653 5 miR-221 TCF12 Hs.511504 5 GO;7275 GO:6955 GO:7517 GO:45449 GO:6357 GO:3677 GO:3702 GO:30528 GO: 5634 miR-221 MESDC1 Hs.513071 5 miR-221 KHDRBS 2 Hs.519794 5 miR-221 C20orf23 Hs.101774 4 GO:7242 GO:7018 GO:5524 GO:3777 GO:166 GO:5874 GO:5875 miR-221 SLC25A3 7 Hs.122514 4 60 200912002

miR-221 MAPK10 Hs. 125503 4 Apoptosis; Apoptosis; G13 signaling pathway; Integrin-mediated cell adhesion; MAPK cascade pathway (Cascade); Wnt signaling miR-221 ARF4 Hs.148330 4 1 Cholera - Infection 05110 GO: 6888 GO: 6886 GO: 7264 GO: 5525 GO: 3924 GO: 8047 GO: 166 GO: 5795 miR-221 VAPB Hs. 182625 4 GO: 6461 GO: 5554 GO: 5198 GO: 5887 miR-221 DMRT3 Hs.189174 4 miR-221 PCDHA6 Hs.199343 4 GO:7155 GO:7156 GO:7399 GO:5509 GO-.5515 GO:5887 GO: 16020 miR-221 NLK Hs.208759 4 miR-221 FOS Hs.25647 4 B cell receptor signaling pathway 04626; MAPK signaling pathway 04010; T cell receptor signaling pathway 04660; Toll-like receptor signaling pathway 04620 GO: 6306 GO: 6954 GO: 6357 GO: 3677 GO:3704 GO:5634 miR-221 DHDDS Hs.369385 4 Nitrogen-linked glycan (N-Glycan) Biosynthesis 00510 GO:8152 GO:16740 miR-221 ATP1A1 Hs.371889 4 GO:15991 GO:6812 GO:30641 GO :8152 GO:6813 GO:6814 GO:30317 GO:5524 GO:15662 GO:16787 GO: 16820 GO:287 GO: 15077 GO: 166 00:30955 GO:5515 GO:31402 GO:5391 G0: 16020 GO: 5624 GO: 5890 61 200912002 Ο

62 200912002

63 200912002

04640; T cell receptor signaling pathway 04660 GO:7155 GO:6955 GO:45086 GO:7169 GO:5515 GO:4888 GO:8270 GO:5886 miR-221 GABRA1 Hs.175934 3 Neuroactive Ligand-Receptor Interaction 04080 GO:6821 GO:7214 GO:6811 GO:4890 GO:5230 GO:5216 GO:30594 GO:5887 GO:45211 miR-221 C1QDC1 Hs.234355 3 miR-221 CDKN1B Hs.238990 3 Cell Cycle 04110 G0: 7050 GO:8285 GO:79 GO:4861 GO:5515 GO:5072 GO:5737 GO:5634 miR-221 TRPS1 Hs.253594 3 GO:6607 GO:6355 GO:1501 GO:6350 GO:6366 GO:46872 G0: 3700 GO: 8270 GO: 5634 miR-221 DNAJC14 Hs.253844 3 miR-221 PGGT1B Hs.254006 3 GO: 18348 GO: 4662 GO: 46872 GO: 4659 GO: 16740 GO: 8270 GO: 5593 miR-221 MYOIC Hs. 286226 3 GO:5524 GO:3779 GO:5516 GO:3774 GO:166 GO:16459 GO:16461 miR-221 SEC24B Hs.292472 3 GO:6888 GO:6886 GO:16192 GO:5515 GO:5215 GO:30127 GO -5795 GO:5783 G0:16020 miR-221 RAB1A Hs.310645 3 GO:6888 GO: 15031 GO:7264 GO:5525 GO:166 GO;5795 GO:5783 miR-221 ASB7 Hs.31845 3 GO:7242 miR- 221 LOC1457 Hs.31845 3 64 200912002

58 miR-221 ZFHX1B Hs.34871 3 TGF Beta message path miR-221 HRB Hs.352962 3 GO:6406 GO:43087 GO:6810 GO:3677 GO:3723 GO:46872 GO:5515 GO:8270 GO:5643 GO :5634 miR-221 EXOC8 Ks.356198 3 miR-221 CTCF Hs.368367 3 GO:45786 GO:122 GO:45893 GO:6350 GO:3702 GO:46872 GO:3676 GO:3714 G0:3700 GO:8270 GO: 5634 miR-221 MY01E Hs.370392 3 G0:30048 GO:5524 GO:42623 GO:3779 GO:5516 GO: 146 GO: 166 GO:16459 miR-221 PRDM2 Hs.371823 3 GO:6355 GO:46872 GO:3676 G0:3700 GO: 8270 GO:5634 miR-221 APG7L Hs.373959 3 miR-221 ATG7 Hs.373959 3 miR-221 VGLL4 Hs.373959 3 GO:6355 GO:6350 GO:5634 miR-221 IRF2 Hs.374097 3 Apoptosis GO:8283 GO:6955 GO: 122 GO:6355 GO:6350 GO:3702 G0:3700 GO:5634 miR-221 DAPK1 Hs.3 80277 3 GO:6915 GO:8624 GO:6468 GO:7243 GO: 7165 GO: 5524 GO: 4685 GO: 5516 GO: 4684 GO: 166 GO: 15629 65 200912002 GO: 4674 GO: 16740 miR-221 BMF Hs.386140 3 Apoptosis 109581 GO: 6915 GO: 5515 GO: 16459 miR- 221 PAEP2 Hs.396644 3 〇〇:45947 GO:6445 GO:5515 GO:30371 G O:5737 miR-221 EIF3S1 Hs.404056 3 Gene expression 74160; translation 72766 GO:6412 GO:6446 GO:5515 GO:3743 GO:5852 miR-221 OGT Hs.405410 3 Grey liquid bile lipid biosynthesis-lactose series 00601; blood type glycolipid biosynthesis - new lactose series 00602; fructose and mannose metabolism 00051; ganglioside biosynthesis 00604; erythrocyte glucoside lipid metabolism 00603; glycerolipid metabolism 00561; glycosphingolipid metabolism 00600; high mannose N-Glycan biosynthesis 00513; N-Glycan biosynthesis 00510; O-Glycan biosynthesis 00512 GO: 6493 GO: 7584 GO: 7165 GO: 8375 GO: 5488 GO: 5515 GO: 16757 GO: 5829 GO: 5634 miR-221 CPNE8 Hs.40910 3 miR-221 PBX3 Hs.428027 3 GO: 7387 GO: 9790 G0: 30902 GO: 7388 GO: 6355 GO: 45898 GO:5515 00:3700 GO:5634 miR-221 ZFPM2 Hs.431009 3 GO:6357 GO:6350 GO:3677 GO:3702 GO:46872 GO:3714 GO.8270 GO:5634 miR-221 ANKHD1 Hs.434219 3 Translation Factor miR-221 RIMS3 Hs.434924 3 GO:6887 GO:45202 66 200912002

GO:6836 miR-221 ATXN1 Hs.434961 3 GO:3723 GO:5737 GO:5634 miR-221 EPB41L1 Hs.437422 3 miR-221 POLH Hs.439153 3 GO:3723 GO:5737 GO:5634 miR-221 HOXCIO Hs .44276 3 GO:9653 GO: 8284 GO:6355 GO:3702 G0:3700 GO:5634 miR-221 Transcribe d locus Hs.446484 3 miR-221 IQCK Hs.460217 3 miR-221 OSBPL7 Hs.463320 3 GO:6869 GO: 8202 GO: 3676 miR-221 DOCKIO Hs.46578 3 GO: 5525 GO: 51020 GO: 5488 GO: 5085 GO: 4872 miR-221 MYO10 Hs.481720 3 GO: 7165 GO: 5524 GO: 3779 GO: 3774 GO : 166 GO:5856 GO: 16459 miR-221 PAIP1 Hs.482038 3 Translation factor GO:48255 GO:45946 GO:6413 GO:3723 GO:5515 GO:8494 GO:5737 miR-221 PAIP1 Hs.482038 3 Translation factor miR -221 MYLIP Hs.484738 3 Tryptophan metabolism 00380 GO: 6928 GO: 7399 GO: 16567 GO.8092 GO: 16874 GO: 46872 GO: 4842 GO: 8270 GO: 5737 GO: 5856 G0: 16020 GO: 151 miR- 221 POGZ Ks.489873 3 GO:7275 GO:3677 GO:46872 GO:3676 GO:8270 GO:5634 67 200912002

miR-221 VDAC3 Hs.491597 3 Calcium ion signal transmission path 04020 GO: 15853 GO:6820 GO: 15482 GO:8308 GO:5887 GO:5741 GO:5739 miR-221 PLS3 Hs.496622 3 GO:3779 GO:5509 GO :5515 GO:15629 miR-221 NAVI Hs.497369 3 GO:6306 GO:6810 GO:5524 GO:3677 GO:17111 GO:166 miR-221 KCNK2 Hs.497745 3 GO:6811 GO:6813 GO:3824 GO: 5216 GO: 15271 GO: 5267 GO: 30955 GO: 5244 GO: 16021 (50:16020 miR-221 INA Hs.500916 3 miR-221 GALNTL 4 Hs.501911 3 Oxygen-linked glycan (O-Glycan) Biosynthesis 00512 GO :5509 GO:30145 GO:4653 GO:5529 GO:16740 GO:16757 GO:5795 GO:16021 miR-221 QKI Hs.510324 3 GO:3676 miR-221 YWHAG Hs.520974 3 Cell cycle 04110 G0:7010 GO: 43066 GO: 6469 GO:7088 GO:45664 GO:9966 GO:48167 GO:3779 GO:5159 GO:19904 GO:42803 G0:5080 GO:8426 GO:5737 miR-221 ANGPTL 2 Hs.521731 3 GO:7275 GO :5102 GO:5615 miR-221 TP53BP2 Hs.523968 3 GO:6915 GO:74 GO:7165 G0:5070 GO:5515 GO:5737 miR-221 VASH1 Hs.525479 3 GO:7049 G0:7050 68 200912002

miR-221 PPARGC1 A Hs.527078 3 Adipocyte hormone signaling pathway 04920; insulin signaling pathway 04910 GO: 8380 GO: 30521 GO: 50873 GO: 1678 GO: 45333 GO: 7586 GO: 19395 GO: 6094 GO: 6397 G0 :7005 GO:46321 GO:45722 GO:35066 GO:45893 GO:6461 GO:50821 GO:42594 GO:1659 GO:6350 GO:6367 GO:3677 GO:3723 GO: 16455 GO:50681 00:30374 GO: 166 GO:8134 GO:5665 GO:5634 miR-221 SOCS3 Hs.527973 3 Adipocyte Hormone Message Transduction GO:7259 GO:4860 Path 04920; Insulin News GO:6916 Interest Conduction Path 04910; GO:7242 Jak-STAT Message Conduction Path GO: 9968 04630; Type 2 diabetes GO: 1558 04930 miR-221 HIPK1 Hs.532363 3 GO: 6468 GO: 5524 GO: 5634 GO: 6355 GO: 16301 GO: 6350 GO: 166 GO: 5515 GO: 4674 GO: 16740 miR-221 GNB3 Hs.534315 3 Energy metabolism 163685 GO: 7186 GO:3924 GO:5834 GO:8217 GO:4871 GO:7165 miR-221 TFR2 Hs.544932 3 GO:6879 GO:8233 GO:5887 GO:6826 GO:4872 69 200912002

GO:6508 GO:4998 miR-221 SLC4A4 Hs.5462 3 GO:6820 GO:6810 GO:5452 GO:8510 GO:16021 GO:5887 GO: 16020 miR-221 MAGI1 Hs.567389 3 dentate nuclear red nucleus Atrophy 05〇5〇; close joint 04530 GO:7155 GO:7166 GO:6461 GO:5524 GO:16301 GO:166 GO:8022 GO:16740 GO:5886 GO:5923 miR-221 PAIP1 Hs.567929 3 Translation factor miR-221 ADAM11 Hs.6088 3 GO:7229 GO:6508 GO:5178 GO:4222 GO:16021 GO:5886 miR-221 RALA Hs.6906 3 GO:6935 GO:6886 GO:7165 GO:7264 GO:5525 GO :166 GO:5515 miR-221 PSMD8 Hs.78466 3 Proteasome 03050; cell cycle 69278; cell cycle checkpoint 69620; DNA Replication 69306 GO:6508 GO:74 GO:5829 GO:5838) miR-221 ANGPTL 4 Hs. 9613 3 GO:1525 GO:30154 GO:9267 GO:43066 G0:51005 GO:45766 GO:45834 GO:1666 GO:4857 GO:5576 miR-221 FAM13A1 Hs.97270 3 miR-221 NTF3 Hs.99171 3 MAPK Message Conduction path 04010 GO: 6916 GO: 6928 GO: 7267 GO: 7399 GO: 7165 GO: 8083 miR-221 RSBN1L Hs592289 3 miR-137 SON Hs.517262 5 GO: 6916 GO: 3677 GO: 3725 GO: 8372 GO: 5622 70 200912002

GO:3676 GO:5634 miR-137 ARID4B Hs.533633 4 GO:3677 GO:3676 G0.5622 miR-137 CA7 Hs.37014 4 Nitrogen Metabolism 00910 GO:6730 GO:4089 GO: 16829 GO:46872 GO:8270 miR -137 CADPS Hs.127013 4 GO:6887 GO:5829 miR-137 CLPX Hs.113823 4 GO:6457 GO:15031 GO:5524 GO:42623 GO:46872 GO: 166 GO:51082 GO:8270 GO:5739 miR- 137 COCH Hs.21016 4 GO:7605 miR-137 CPNE8 Hs.40910 4 miR-137 CPSF6 Hs.369606 4 GO:6397 GO:3723 GO:166 GO:5634 miR-137 DHX40 Hs.29403 4 miR-137 DUSP4 Hs .417962 4 mapk message path 04010 GO: 165 GO: 6470 GO: 74 GO: 17017 GO: 16787 GO: 4725 GO: 8330 GO: 5634 miR-137 EPHA7 Hs.73962 4 Axon guidance 04360 GO: 6468 GO: 7169 GO:5524 G0:5003 GO:166 GO:5515 GO:4872 GO:16740 GO:16021 G0:16020 miR-137 ESRRA Hs.110849 4 Nuclear Receptor s GO:6355 GO:6350 GO:46872 GO:5496 GO :3707 G0:3700 GO:8270 GO:5634 miR-137 FKBP4 Hs.524183 4 Calcium ion signal path GO:6457 GO:5528 GO: 16853 GO:3755 GO:5737 GO:5634 71 200912002

GO:30674 miR-137 FURIN Hs.513153 4 Notch message path GO:7267 GO:5509 GO:5794 157118 ; 00:6508 GO:4276 GO: 16021 Post-translational GO:8233 G0.30140 modtfication of protein 00:4289 163841 miR-137 HLF Hs. 196952 4 GO:7275 QO:3690 GO:5634 GO:6355 GO:48511 00:6350 GO:6366 miR-137 HMGN3 Hs.77558 4 GO:4 GO:3677 GO:785 GO:46966 GO: 5634 miR-137 INPP5A Hs.523360 4 Inositol sulphate metabolism GO: 7154 GO: 16787 GO: 16020 00562; phospholipid osmolarity message GO: 4437 Conduction system 04070 GO: 4445 miR-137 NMNAT3 Hs.208673 4 miR-137 NY-SAR- Hs.348418 4 41 miR-137 PPP3CB Hs.500067 4 Apoptosis 04210; Axon GO: 6470 GO: 74 GO: 5509 GO: 5955 Guidance 04360; B cell receptor GO: 7165 GO: 5516 message path 04462; G0.6351 GO: 16787 calcium ion signal path GO: 5506 〇 4020; MAPK message GO: 4722 path 04010; natural killer cell cytotoxicity 04650; T cell receptor message Path 04660; Wnt message path 04310 GO: 8270 miR-137 PTPN2 Hs.123352 4 Calcium ion signaling path; GO: 6470 GO: 16787 Type 1 diabetes GO: 4725 GO: 4872 miR-137 SYT1 Hs.310545 4 miR -137 TDRD7 Hs.193842 4 miR-137 WIFI Ks.284122 4 Wnt message path GO: 16055 GO:4713 04310 GO:7267 GO:7275 72 200912002

00:7165 miR-137 ZC3H6 Hs.190477 4 miR-137 ABHD6 Hs.476454 3 GO:6725 GO:16787 miR-137 ACSL6 Hs.14945 3 Adipocyte Hormone Message Transduction GO:6637 GO: 16874 GO:16021 Path 04920; Fatty acid GO: 6629 GO: 4467 GO: 5792 Metabolism 00071 GO: 8152 GO: 287 GO: 5741 00: 5778 GO: 5886 miR-137 ACVR1 Hs. 470316 3 Cytokines - Cytokines by GO: 6468 GO: 5524 GO: 5887 body interaction 04060; TGF-beta GO: 7178 GO: 287 GO: 16020 message path 05350 GO: 30145 GO: 166 GO: 4713 GO: 4872 GO: 16740 GO: 5024 miR-137 AP3S1 Hs.406191 3 GO: 8286 00:5215 CjO:5795 GO:6886 GO:30125 GO:6810 GO:30119 GO:30133 miR-137 ATBF1 Hs.569686 3 miR-137 ATP1B1 Hs.291196 3 Trans-ion regulation in heart fine GO:6813 00:30955 00 :16021 Cell; Metabolism GO:6814 GO:31402 GO: 16020 GO:6810 GO:5391 GO:5890 miR-137 ATXN1 Hs.434961 3 miR-137 POLH Hs.439153 3 GO:3723 GO:5737 GO:5634 miR -137 BACH2 Hs.269764 ~ — 3 GO:6355 GO:3 677 GO:5634 GO:6350 GO:5515 miR-137 C5orfl3 Hs.483067 3 miR-137 CABLES2 Hs.301040 3 miR-137 CACNA1 G Hs. 194746 3 Calcium ion signal path GO:6816 GO:5509 GO:16021 04020 Type 2 Diabetes GO:6812 GO:5261 G0:16020 04930 GO:8332 GO:5624 GO:5245 GO-.5891 miR-137 CHESl Hs.434286 3 GO:77 GO:85 GO:5515 GO:5634 -- —--1 ^---- 73 200912002

GO: 6355 GO.-6350 G0; 3700 miR-137 CHST9 Hs.567604 3 Cysteine Metabolism 〇〇 272 G0.5975 GO: 7417 G0: 30203 GO: 42446 GO: 6790 GO: 1537 GO: 16740 GO: 5795 GO: 16021 GO:31228 miR-137 CRSP2 Hs.407604 3 GO:30521 00:45944 GO:6350 GO:6367 GO:16455 GO:30374 GO:4872 GO:46966 GO:42809 GO:119 GO:5634 miR-137 CSDA Hs. 221889 3 Tight joint 04530 GO: 122 GO: 6355 GO: 9409 GO: 6350 GO: 3677 GO: 3702 GO: 3690 GO: 3714 G0: 3700 GO: 5737 GO: 5634 miR-137 CSE1L Hs.90073 3 GO: 6915 00 :8283 GO:59 GO:1503I GO:5488 GO:8262 GO:8565 00:5737 GO:5643 GO:5634 miR-137 CUL3 Hs.372286 3 Ubiquitin Media Protein Hydrolysis 04120 GO:82 GO:7049 G0:7050 GO:8629 GO:8284 GO:6512 GO:5515 GO:5634 miR-137 DCDC2 Hs.512603 3 GO:6968 GO:7242 GO:1764 miR-137 DMRT2 Hs.59506 3 GO:8584 GO:6355 GO :7530 GO:7548 GO:6350 GO:46872 00:3700 GO:8270 GO:5634 miR-137 DUSP8 Hs.41688 3 MAPK message path 04010 GO: 188 GO:6470 GO:17017 GO:16787 GO:4725 GO: 5737 GO: 5634 miR-137 DYRK1A Hs.368240 3 Coenzyme (CoA) bonded GO: 7399 GO: 5524 GO :5634 74 200912002

Benzoate degradation 00632; inositol phosphate metabolism 00562; nicotinic acid and smoke test guanamine metabolism 00760; phospholipid kinsin signaling system 04070 GO:18108 GO:4715 GO:166 GO:4674 GO: 16740 miR -137 EIF2C1 Hs.22867 3 GO:6412 GO:6446 GO:5515 GO:3743 GO:5850 miR-137 ENC1 Hs. 104925 3 GO:7275 GO:7399 GO:3779 GO:5515 GO:5856 GO:5634 miR- 137 EPAS1 Hs.468410 3 GO: 1525 GO:30154 GO:6355 GO:1666 GO:7165 GO:6366 GO:3705 GO:35035 GO:5515 GO:4871 GO:3713 GO:5634 miR-137 EPHA4 Hs.371218 3 Axon guidance 04360 GO: 6468 GO: 7165 GO: 7169 GO: 5524 G0: 5003 GO: 166 GO: 4674 GO: 4872 GO: 16740 GO: 5887 GO: 16020 miR-137 ERG Hs. 473819 3 GO: 8283 GO :7275 GO:6468 GO:6355 GO:7165 GO:6350 GO:5515 GO:4871 G0:3700 GO:5634 miR-137 ESRRG Ks.444225 3 GO:7275 GO:45893 GO:6350 GO:50682 GO:5516 GO :46872 GO:5496 GO:3707 G0:3700 GO:16563 GO:8270 GO:5634 miR-137 FAM77C Hs.470259 3 75 200912002 miR-137 GABRA1 Hs. 175934 3 Neuroactive Ligand-Receptor Interaction 04080 GO: 6821 GO: 7214 GO: 6811 GO: 4890 GO; 5230 GO: 5216 GO: 30594 GO: 5887 GO: 4 5211 miR-137 GPR85 Hs. 152009 3 GPCRDBA-type rhodopsin GO: 7186 GO: 7165 GO: 4872 GO: 1584 GO: 16021 miR-137 GPR88 Hs. 170053 3 GPCRDB other types GO: 7186 GO: 7165 GO: 16526 GO:4872 GO:1584 GO:8372 GO:16021 miR-137 IFT20 Hs.4187 3 GO:19861 miR-137 ITPR3 Hs.93235 3 Calcium ion regulation in heart cells; smooth hunger contraction miR-137 KIAA201 0 Hs.533887 3 GO: 15986 GO:6817 GO:5488 GO:46933 GO:46961 GO:5737 GO: 16020 GO:16469 miR-137 LGR4 Hs.502176 3 GO:7186 GO:7165 GO: 16500 GO:4872 GO: 16021 miR-137 LRRN3 Hs.3781 3 miR-137 MITF Hs.166017 3 GO:7275 GO:30318 GO:6355 GO:7605 GO:3677 GO:16563 GO:5634 miR-137 MTPN Hs.43297 3 miR-137 MYBPC1 Hs.567306 3 Striated muscle contraction miR-137 NAB2 Hs. 159223 3 GO:8283 GO:16481 GO:7399 GO:6355 GO:6350 30:3714 GO:5634 miR-137 NRP1 Hs. 131704 3 Axon guidance 04360 GO:1525 GO:7411 GO:7155 GO:30154 GO:7267 GO:7399 GO:9887 GO:8284 GO:4872 GO:5021 GO:16021 G0:16020 GO:5624 76 200912002 —-— ---- miR-137 OXSR1 Hs.475970 - -- GO:7165 3 sentences away Message conduction path; GO: 6468 GO: 5524 Sesame fat inositol message transmission system GO: 7243 GO: 287 GO: 166 Practice GO: 6979 GO: 5515 GO: 4674 GO: 4713 miR-137 PDLIM3 Hs.85862 --- ~ — GO: 16740 3 GO:46872 GO:5515 miR-137 PHF15 ------- UU:oZ/U iy 3 GO:6355 GO:5515 miR-137 PITPNA Hs.429819 — CjU:o270 3 GO: 6629 GO:8289 GO:5622 GO:6810 GO:8525 GO:7601 GO:8526 miR-137 PLEKHA 5 Hs.188614 3 GO:4 GO:5545 GO:8372 miR-137 PPM1E Hs.245044 3 Calcium ion conduction path miR-137 PTGFRN Hs.418093 3 miR-137 RANBP2 Hs. 199561 3 GO:46907 GO:8536 GO:5643 GO:6457 GO:5488 GO:5634 GO:6606 GO:16853 GO:46872 GO:3755 GO:8270 miR -137 RBM12 Hs.246413 3 miR-137 RPS13 Hs.446588 3 ribosome 03010; gene expression 74160; translation 72766 GO: 6412 GO: 3735 GO: 5840 tniR-137 RWDD4A Hs.133337 3 miR-137 SGCG Hs.37167 3 GO:7010 GO:5856 GO:7517 GO:16021 GO:5886 GO:16012 miR-137 SH3BP5 Hs. 257761 3 GO:7242 30:17124 □0:5739 G0:5070 GO:5515 77 200912002

GO: 4860 miR-137 SIPA1L2 Hs.268774 3 GO: 5096 GO: 5515 miR-137 SLC17A6 Hs.242821 3 miR-137 SLC25A5 Hs.522767 3 Calcium ion signal path GO: 6839 GO: 15207 GO: 5SS7 04020; Glycosidic acid metabolism GO: 6810 GO: 5488 GO: 5743 15869 GO: 5215 GO: 5739 miR-137 SLC43A2 Hs. 160550 3 miR-137 SLC6A15 Hs.44424 3 GO: 6836 GO: 5328 G0.5SS7 GO: 15293 GO: 16020 miR-137 SLC7A9 Hs.408567 3 GO:6520 GO:15184 GO:5887 GO:6865 GO:5279 GO:5886 GO:6461 GO:6810 miR-137 SNX25 Hs.369091 3 GO:7242 GO:4871 miR-137 SRPK1 Hs.443861 3 mRNA synthesis regulation GO: 30154 GO: 5524 GO: 5737 GO: 7059 GO: 287 GO: 166 GO: 5634 GO: 398 GO: 5515 GO: 6468 GO: 4674 GO: 7243 GO: 16740 GO: 50684 miR -137 ST18 Hs.147170 3 GO:6355 G0:3700 GO:5634 miR-137 STX16 Hs.307913 3 SNARE in vesicle transport GO:6891 GO:8565 GO:5795 Interactive 04130 GO:6886 GO:5486 GO:16021 G0:16020 GO:5792 miR-137 SV2A Hs.516153 3 ECM-Receptor Interaction 04512 GO:6810 GO:15293 GO: 1602 1 GO:5215 G0:16020 miR-137 TARDBP Hs.300624 3 GO:7067 GO:3723 GO:5634 GO:398 GO:8017 GO:6355 GO: 166 GO:6350 GO:5515 GO:6366 G0:3700 miR- 137 TBC1D19 Hs.567531 3 GO:5096 miR-137 TCF12 Hs.511504 3 miR-137 THBS4 Ks.211426 3 Cell Signaling 01430; GO:7155 GO:5509 GO:5578) 78 200912002

ECM-receptor interaction 04512; focus attachment 04510; TGF-beta message path 04350; hemostasis 109582 GO: 6930 GO: 8201 GO: 5515 GO: 5I98 miR-137 THRAP1 Hs.282678 3 GO:30521 GO:45944 GO:6355 GO:6350 GO:6367 GO: 16455 GO:30374 GO:4872 GO:46966 GO:42809 GO: 119 GO:5634 miR-137 TRPS1 Hs.253594 3 GO:6607 GO:6355 GO:1501 GO:6350 GO:6366 GO:46872 G0:3700 GO:8270 GO:5634 miR-137 TSSK3 Hs.512763 3 GO:30154 GO:7242 GO:6468 GO:48240 GO:7283 GO:5524 GO:166 GO:4674 GO:4713 GO: 16740 GO: 5622 miR-137 UGP2 Hs.516217 3 galactose metabolism 00052; nucleotide sugar metabolism 00520; pentose and glucuronate interconversion 00040; starch and sucrose metabolism 00500; carbohydrate metabolism 71387 GO: 6011 GO: 8152 GO :3983 GO:16301 GO:16740 * Predicted by at least three of five algorithms (PicTar, TargetScan, Miranda, MirBase, and CRSD) **GO (Gene Ontology): Provides information and descriptions of genes and gene products Library.分析 Analyze according to KEGG ( http : //www.genome_jp/kegg/ ), GenMAPP ( http : //www.genemapp.org/ ) and Reactome ( http : //www.reactome.org/) Table 7: Subject to micro Prediction path for ribonucleic acid effects 79 200912002

Path 数 Number of micronuclear RNA predictions 卞ΜΑΡΚ message transmission path hsa-let-7a 55 9.0E-24 hsa-miR-372 22 5.5E-06 hsa-miR-182* 9 3.0E-05 hsa-miR -221 15 4.1E-04 hsa-miR-137 13 1.7E-03 Adipocyte hormone signaling pathway hsa-miR-182* 6 2.7E-06 hsa-miR-221 9 8.6E-06 hsa-miR-137 6 1.5E-03 hsa-miR-372 7 2.3E-03 hsa-let-7a 6 4.2E-02 VEGF signal transduction pathway hsa-miR-372 11 5.2E-06 hsa-miR-182* 5 7.0E-05 hsa -let-7a 9 2.0E-03 hsa-miR-137 4 4.6E-02 Wnt message path hsa-miR-372 22 4.3E-10 hsa-let-7a 21 8.3E-07 tisa-miR-182* 6 3.2E-04 tisa-miR-221 8 1.4E-02 Type 2 diabetes isa-miR-221 6 2.6E-04 [isa-miR-137 5 1.3E-03 bisa-let-7a 7 1.5E-03 isa -miR-182* 3 2.2E-03 Focus attached to tisa-let-7a 37 3.2E-13 isa-miR-182* 5 1.1E-02 isa-miR-221 10 1.8E-02 Adhesive joint isa-let-7a 16 1.3E-05 isa-miR-221 6 3.1E-02 isa-miR-372 7 4.0E-02 Axon guidance isa-miR-137 20 3.1E-12 isa-let-7a 26 6.2E-11 isa -miR-372 19 1.4E-08 B cell receptor message transmission Path hsa-miR-372 11 9.6E-07 hsa-let-7a 12 4.5E-06 hsa-miR-137 4 2.7E-02 calcium ion conduction path message hsa-miR-372 22 1.0E-08 80 200912002

*List only the five microRNAs explored by the present invention, at least three of which are analyzed by GeneSpring software. hsa-let-7a 25 7.6E-08 hsa-miR-137 11 7.5E-04 Cell cycle hsa-miR -372 17 3.5E-09 hsa-miR-221 9 2.4E-04 hsa-let-7a 9 1.7E-02 ECM-receptor interaction hsa-let-7a 27 6.0E-16 hsa-miR-372 9 1.1E -03 hsa-miR-182* 4 2.3E-03 Epithelial cell signaling in Helicobacter pylori air-staining hsa-miR-221 7 6.1E-05 hsa-miR-182* 4 2.0E-04 Hsa-let-7a 5 3.9E-02 Insulin asphyxiation pathway hsa-miR-221 9 1.6E-03 hsa-miR-182* 4 7.8E-03 hsa-let-7a 10 3.2E-02 Long-term gain effect hsa -miR-372 12 1.6E-06 hsa-let-7a 12 5.1E-05 hsa-miR-137 5 1.5E-02 (f) Kaplan-Meier survival prospect analysis of microribonucleic acid characteristics consisting of three microribonucleic acids Using the Kaplan-Meier survival prospect analysis, it was found that the microribonucleic acid characteristics consisting of three microRNAs hsa-miR221, hsa-miR372 and hsa-miR137 were also associated with post-treatment viable cancer in patients. It can be found from the results of the analysis that these results are statistically significant. Training data set (n = 56): In the overall survival prospect analysis, cadaver value = 〇.〇〇13 In the analysis of non-recurring survival prospects, cadaver value = 0.0437 test data set (n = 56): 81 200912002 overall survival In the prospective analysis, ρ.〇1468 was analyzed in the prospect of non-recurring survival, /> value = 0.0841 independent cohort (n = 62): In the overall survival prospect analysis, household value = 〇〇359 in the prospect of non-recurring survival Medium, household value = 〇〇 985 training data set and test data set (n = U2): In the overall survival prospect analysis, household value = 〇〇〇 11 In the analysis of non-recurring survival prospects, household value = 〇〇 119 P-values were obtained from log-rank tests to examine different survival prospect curves between high-risk and low-risk patient groups. Other Embodiments All of the features disclosed in the present specification can be arbitrarily combined. Each feature disclosed in this specification can be replaced with an alternative feature that achieves the same, equivalent, or similar purpose. Therefore, unless expressly stated to the contrary, the features disclosed are only the embodiment of the above-described concept of the equivalent of a series of equivalent or similar features. The present invention has been described above in terms of preferred embodiments, and is not intended to limit the invention, and various modifications and refinements may be made without departing from the spirit and scope of the invention. For example, a structurally equivalent compound with a oxadiazole compound can also be formed and screened to carry out the above-described embodiments of the present invention. Therefore, the scope of the invention is defined by the scope of the appended claims. FIELD OF THE INVENTION The above and other objects, features, advantages and embodiments of the present invention will become more <RTIgt; <RTIgt; </ RTI> <RTIgt; </ RTI> <RTIgt; The analysis was performed based on the expression levels of hsa-miR137, hsa-miR372, hsa-miR182*, hsa-miR221, and hsa-let-7a in 112 NSCLC patients. Figure 1A illustrates the micro-ribonucleic acid risk score distribution map. Figure 1B illustrates the death/survival status of the patient. Figure 1C illustrates the microRNA expression analysis of patients; the bottom to top are hsa-let-7a, hsa-miR221, hsa-miR372, hsa-miR182*, and hsa-miR137, respectively; Suffering. The dotted line indicates the segment (risk score 7.1), which differentiates the patient into a low risk and a south risk group. Figure 2 is a Kaplan-Meier assay to estimate the overall survival status and non-recurrence status of NSCLC patients at low risk and high risk. Figures 2A, 2B, and 2C illustrate the estimated results from 56 patients in the training data set, 56 patients in the test data set, and 62 patients in the independent peer group. Figure 3 is a Kaplan-Meier assay to estimate the overall survival and non-recurrence status of NSCLC patients at low risk and high risk. Figures 3A, 3B, 3C, 3D, and 3E illustrate the first phase of NSCLC patients (n = 47), the second phase of NSCLC patients (n = 28), and the third phase of NSCLC, respectively. Estimated results from patients (n=37), adenocarcinoma patients (n=55), and squamous cell carcinoma patients (n=50). 83 200912002 [Main component symbol description]

Claims (1)

200912002 X. Patent application scope: 1. A method for predicting the survival prospect of a cancer patient after treatment, the method comprising: detecting microRNAs hsa-miR137, hsa-miR372 in a cancer patient treated The amount of performance of hsa-miR182*, hsa-miR221 and hsa-let-7a; calculating the risk score of one of the patients based on the amount of micronuclear nucleic acid expression; and determining the cancer disease based on the value of the risk score Survival prospects after treatment. 2. The method of claim 1, wherein the risk integral is calculated as follows: (〇.15xhsa-miR137 performance)+ (031xhsa_miR372 performance)+ (〇.28xhsa_miR182* performance)+ (_ 〇.i3 xhSa-miR221 performance)) (_〇14xlet7a performance). 3. The method of claim 2, wherein the risk score is equal to or less than -7.1 indicating that the patient's survival prospect after treatment is acceptable. 4. The method according to claim 1, wherein the patient suffers from lung cancer, platinum disease, breast cancer, pancreatic cancer, adenocarcinoma, squamous cell carcinoma, colon cancer or hepatocellular carcinoma. The method of claim 1, wherein the patient suffers from non-small cell lung cancer. 6. The method of claim 5, wherein the patient suffers from the first, second or third stage of the non-small cell lung cancer. 7. The method of claim 1, wherein the patient has undergone surgery, chemotherapy, radiation therapy, or a combination thereof. 8. A method for predicting survival after treatment in a cancer patient, the method comprising: detecting a microRNA expression in a cancer patient treated 1 ' wherein the microribonucleic acid is selected from a group consisting of: hsa-miRl37, hsa-miR372, hsa-miR182*, and hsa-miR221; determining one of the microribonucleic acid-dCt values according to the amount of expression of the microribonucleic acid; and according to the microribonucleic acid This _dCt value predicts survival prospects after treatment. 9. The method of claim 8, wherein one of the hsa-miR137-dCt values is equal to or less than 8.22, indicating that the patient's survival prospect after treatment is acceptable. The method of claim 8, wherein a dCt value of one of hsa_miR182#N is equal to or less than _7 83 indicates that the patient's survival prospect after treatment is still available. 86 200912002 Method 11 as claimed in claim 8. The request item August-dCt value is equal to or greater than -0.57. One of hsa-miR221 indicates that the patient’s survival prospect after treatment is still acceptable. The method according to claim 8 is or is less than _ old 5 means that the survival prospect after treatment is acceptable. The patient suffers from lung cancer, squamous cell carcinoma, colon cancer 13 as described in claim 8. Methods Leukemia, breast cancer, pancreatic cancer, adenocarcinoma, or hepatocellular carcinoma. 14. The method of claim 8, wherein the patient suffers from a small The method of claim 14, wherein the patient suffers from the first, second or third stage of the non-small cell lung cancer. The method of claim 8, wherein the patient has undergone surgery/alpha therapy, chemotherapy, radiation therapy, or a combination thereof. 17. A method for predicting survival after treatment in a cancer patient, the method of which includes: detecting the amount of let-7a in a cancer patient treated; determining the amount of performance of the let-7a The one-dCt value of the let-7a; and the post-treatment survival prospect is predicted based on the _dCt value of the let-7a, wherein the -dCt value is equal to or greater than 2.21 indicating that the patient's survival prospect after treatment is acceptable. 18. A method for predicting a post-treatment survival prospect of a cancer patient, the method comprising: detecting the amount of four microRNAs in a treated cancer patient's four microribonucleic acid systems Selected from the group consisting of: hsa-miR137, hsa-miR372, hsa-miR182*, hsa-miR221, and hsa-let-7a; calculating a risk score based on the amount of microRNA expression; and integrating the risk The value determines the survival prospect after treatment. 19. The method of claim 18, wherein the amount of performance of the hsa-miR372, hsa-miR182*, hsa-miR221, and hsa-let-7a is determined and the risk integral is calculated as follows: (〇·31 The performance of X hsa-miR372) + (the performance of 〇·28 x hsa-miR182*) + the amount of performance) + (-0.14X performance amount ofhsa_let_7a); wherein the risk score is equal to or less than -5.90, indicating the patient Survival prospects after treatment are still acceptable. The method of claim 18, wherein the performance amount of the hsa-miR137, hsa-miR182*, hsa-miR221, and hsa-let-7a is determined and the risk integral is calculated as follows: (0.15 The performance of X hsa-miR137) + ( 〇·28 χ hsa-miR182* performance) + (_0.13xhsa_miR221i performance) + (-0·14χ performance 0fhsa-iet-7a); where the risk integral is equal to Or less than -3.71 indicates that the patient's survival prospect after treatment is acceptable. 21. The method of claim 18, wherein the amount of performance of the hsa-miR137, hsa-miR372, hsa-miR221, and hsa-let-7a is determined, and the risk integral is calculated as follows: (0.15xhsa-miR137 The amount of performance) + (〇31xhsa_miR372 (-0.14 performance) + (-0.13xhsa-miR22l performance) χ performance $ of hsa-let-7a); wherein the risk score is equal to or less than _4.87 indicates the patient Survival prospects after treatment are still acceptable. 22. The method of claim 18, wherein the method is determined The survival prospect of the patient after treatment in the form of -7.02 is acceptable for hsa-miR137, hsa-miR182*, 89 200912002 23. The method according to claim 18, wherein the hsa-miR137, hsa-miR182*, The performance of hsa-miR22l and hsa-miR372, and the risk score is calculated as follows: (0.15 X hsa-miR137 performance) + (0.28 x hsa-miR182* performance) + (_〇.i3xhsa_miR22i performance Quantity) + (〇_31 xhsa-miR372 performance); wherein the risk score is equal to or less than -8.66, indicating that the patient's survival prospect after treatment is acceptable. 24. A method for predicting a post-treatment survival prospect of a cancer patient, the method comprising: detecting the amount of hsa-miR221, hsa-miR372, and hsa-miR137 in a treated cancer patient; The amount of performance of the microribonucleic acid is calculated based on a risk score; and the post-treatment survival prospect is determined based on the risk integral value. 25. The method of claim 24 wherein the risk integral is calculated as follows: (〇_15 X hsa-miR137 performance) + (0.315{performance h £ hsa-miR372) + (_0.l3xhsa-miR221 The performance amount); wherein the risk score is equal to or less than -4.7 indicates that the patient's survival prospect after treatment is acceptable. 200912002 26. A kit for detecting microribonucleic acid expression, wherein the kit comprises a plurality of oligonucleotides that can be used to detect the expression of hsa-miR221, hsa-miR372 and hsa-miR137. 27. A kit for detecting microribonucleic acid expression, wherein the kit comprises a plurality of oligonucleotides for detecting the expression of at least four microribonucleic acids selected from the group consisting of The group consisting of hsa-miR137, hsa-miR372, hsa-miR182*, hsa-miR221 and hsa-let-7a. 28. The kit of claim 27, wherein the kit comprises a plurality of oligonucleotides for detecting the hsa-miR137, hsa-miR372, hsa-miR182*, hsa-miR221, and hsa-let- Performance of 7a. 91